Selected Papers By Cse Department

Ref No: 2 RIPPLE-2K7 (A NATIONAL LEVEL STUDENT TECHNICAL SYMPOSIUM)

TITLE: HUMAN COMPUTING & MACHINE UNDERSTANDING OF HUMAN BEHAVIOR Author:

*SOMALA HEM KUMAR

Email:

IV/IV B-TECH

CSE

[email protected] [email protected]

Phone number: 9247218407 (Hem Kumar)

1

ABSTRACT A widely accepted prediction is that computing is moving background projecting the human user into foreground. Today computing has become a key in every technology. If this prediction is to come true, then next generation computing, which we will call as human computing is about anticipatory user interfaces that should be human centered, built for humans based on human model. In the present paper we will discuss how human computing leads to understanding of human behavior , number of components of human behavior, how they might be integrated into computers & how far we are from enabling computers to understand human behavior.

2

Contents: 1. Human computing 2. Facial action detection 3. Approaches to measurement: 3.1……Real time facial expression recognition for natural interaction 3.2……Message judgment 3.3……Sign measurement 4. Research challenges 4.1……Scientific challenges 4.2……Technical challenges 5. Conclusion 6. References

3

HUMAN COMPUTING & MACHINE UNDERSTANDING OF HUMAN BEHAVIOR 1. Human computing: A widely accepted prediction is that computing is moving background, projecting the human user into foreground. Today computing has become a key in every technology .If this prediction is to come true, the next generation computing ,

which we will call

as

human computing is about

anticipatory user interfaces that should be human centered , build for humans based on human model. In human-human interaction , intentions & action tendencies often are more important than what an individual may be feeling .People may or may not aware of what they’re feeling , and feelings often come about sometime late in the emotion. One way of tackling the problems is to move away from computercentered designs toward human-centered designs for HCI. The former involve usually the conventional interface devices like keyboard, mouse, and visual displays, and assume that the human will be explicit .But, a goal of humancentered computing is computer systems that can understand human behavior in unstructured environments & respond appropriately Efforts at emotion recognition however are inherently flawed unless one recognizes that emotion-intentions, action tendencies, appraisals, and feelings-is not an observable. Emotion can only be inferred from context, self report, physiological indicators, and expressive behavior.(see the following figure)

4

Here we will focus on expressive behavior, in particular facial expression, and approaches to measurement.

2. Facial action detection: Numerous techniques have been developed for face detection i.e.…, identifying all regions in the scene that contain a human face. Tracking is the essential step for human-motion analysis since it provides the data for recognition of face head/body postures and gestures.

3.Approaches to measurement: 3.1. Real time facial expression recognition for natural interaction 3.2. Message judgment 3.3. Sign measurement 3.1. Real time facial expression recognition for natural interaction:

5

In this the basic step is facial action detection. The process of facial action detection is as follows. Take a look at the above figure. First, the face image is captured, then the main important features that are needed are extracted . They are then normalized based on the distance between the eyes. Now let us see about behavioral recognition by real time facial expression recognition for natural interaction. Here mainly 5 distances are taken into account. They are distances between right eye & eye brow, left eye & eyelid, left eye & left corner of mouth, width of the mouth, and height of the mouth. Now initially the distances are stored in the database. Now each parameter can take three different states for each of the emotions: C+, C- , and S.

State C+ means that the value of the parameters has increased with respect to the neutral one; state C- that its value has diminished with respect to the neutral one; and the state S that its value has not varied with respect to the neutral one.First, we build a descriptive table of emotions, according to the state of the parameters, like the one of the table below:

6

Now based on the above table we will know the 6 basic emotions of a human. For example: take a look at first row in the above table. Distance D1 must diminish, D2 must be neutral or diminished, D3 must be increased, D4 must be increased, D5 must be diminish, width / height must decrease or neutral to the stored value, in order to exhibit the emotion Joy. Like that all the remaining 5 emotions will be known from the above table.

3.2 Message judgment: Generally all the facial expressions will be given some Action Units (AU’s) (i.e.), all the facial expressions are feeded in computer with some AU’s. Based on those Action Units the corresponding expression is displayed by the computer. There are actually 40 AU’s, but the recent systems can recognize only 15 to 27 AU’s. Generally for each and every part of a face according to the features the Action Units are given to points plotted on the faces (i.e.) FACE FEATURE POINTS. Based on these points the system designates the behavior of a Human. The task is to describe the surface of behavior with the judgment based approach that is making judgments, such as “this face is happy just by seeing a smile on his face.” But where as an observe with a sign based

7

approach would code the face.

Actually there are six “basic emotions.” They are joy, surprise, sadness, disgust, fear and anger. An example of facial expressions for the six basic -motions are shown in the figure above. There are some contradictory emotion expressions, for example consider “MASKING SMILE,” in which smiling is used to cover up or hide an underlying emotion. So such type of underlying emotions can be observed with sign based approach.

3.3 Sign measurement:

Of the various methods, the Facial Action Coding System (FACS) is the most comprehensive, psychometrically rigorous, and widely used. The most recent version of Facial Action Coding System specifies:

8

•

9 Action Units for upper face

•

18 Action Units for lower face

•

11 Action Units for head position and movement

•

9 Action Units for eye position and movement and Action Units may occur singly or in combinations. Action Unit

Combinations may be Additive Combinations or Non-Additive Combinations. In Additive Combinations, the appearance of each Action Unit is Independent, where as in Non-Additive Combinations the Action Units modify each other’s appearance. Non-Additive Combinations are analogous to co-articulation effects in speech, in which one phoneme modifies the sound of one’s with which it is contiguous. An Example of an Additive Combinations in Facial Action Coding System is (AU 1+2), which often occurs in surprise (along with eye widening, AU 5) and in the brow-flash greeting. The combination two Action Units raises the inner (AU 1) and outer (AU 2) corners of the eye brows and causes horizontal wrinkles to appear across the forehead. The appearance changes associated with (AU 1+2) are the product of their joint actions. The Examples of Non-Additive Combinations are (AU 1+4) and (AU 1+2+4), comparable to co-articulation effects in speech. Here (AU 1+4), which often occurs in sadness. When AU 1 occurs alone, the inner eyebrows are pulled upward. When AU 2 occurs alone, they are pulled together downward. When AU 1 and AU 4 occur together, the downward action of AU 4 is modified. The result is that the inner eyebrows are raised and pulled together. This action typically gives an oblique shape to the brows and causes horizontal wrinkles to appear in the center of the forehead, as well as other changes in appearance.

9

4. RESEARCH CHALLENGES 4.1. Scientific challenges: 1. Modalities: We should know how many and which behavioral signals has to be combined for realization of robust and accurate human behavior analysis .Here the behavioral channels includes face, body and tone of the voices of the human. 2. Fusion: Here the main challenge is to know at what abstraction level the input modalities have to be fused. We should know whether the input modalities depend upon the machine learning techniques or not .One should know whether the tight coupling persists when the modalities are used for the human behavior analysis.

4.2. Technical challenges: For understanding of human behavior we should meet the technical challenges which are as follows.

1 .Robustness: Most methods for human sensing, context sensing and human behavior understanding works only in the constrained environments. Here the environment should be very calm without any noise. If the environment is noisy then it causes them to fail.

10

2. Speed: Many of the methods in the field do not perform fast enough to support interactivity. Speed of the signals should be fast enough to the destination point. Many of the researchers choose for more sophisticated processing rather than for real time processing .The main challenge is to find faster hardware

5. CONCLUSIONS Human behavior understanding is a complex and very difficult problem. It is still far from being solved in a way which is suitable for anticipatory interfaces and human computing application domain. In the past two decades there has been significant progress in some parts of the field like face recognition and the video surveillance .While in the other parts of the field it is non basic affective state recognition and multimodal multi-aspect context-sensing. Although there remain significant, scientific and technical issues to be addressed, it is optimistic about future progress in the field. The main reason is that anticipatory interfaces and their applications are likely to become the single most widespread research topic of artificial intelligence and human computer interaction research communities Now there are a large and steadily growing number of researches Projects which are concerned with the interpretation of the human behavior at a deeper level.

11

6. REFERENCES: [1] Aarts, E. Ambient intelligence drives open innovation. ACM Interactions, 12, 4 (July/Aug. 2005), 66-68. [2] Ambady, N. and Rosenthal, R. Thin slices of expressive behavior as predictors of interpersonal consequences: A meta-analysis. Psychological Bulletin, 111, 2 (Feb. 1992), 256-274. [3] Ba, S.O. and Odobez, J.M. A probabilistic framework for joint head tracking and pose estimation. In Proc. Conf. Pattern Recognition, vol. 4, 264-267, 2004. [4] Bartlett, M.S., Littlewort, G., Frank, M.G., Lainscsek, C.,Fasel, I. and Movellan , J. Fully automatic facial action recognition in spontaneous behavior. In Proc. Conf. Face &Gesture Recognition, 223-230, 2006. [5] Bicego, M., Cristani, M. and Murino, V. Unsupervised scene analysis: A hidden Markov model approach. Computer Vision & Image Understanding, 102, 1 (Apr. 2006), 22-41. [6] Bobick, A.F. Movement, activity and action: The role of knowledge in the perception of motion. Philosophical Trans. Roy. Soc. London B, 352, 1358 (Aug. 1997), 1257-1265. [7] Bowyer, K.W., Chang, K. and Flynn, P. A survey of approaches and challenges in 3D and multimodal 3D+2D face recognition. Computer Vision & Image Understanding, 101, 1 (Jan. 2006), 1-15. [8] Buxton, H. Learning and understanding dynamic scene activity: a review. Image & Vision Computing, 21, 1 (Jan.2003), 125-136. [9] Cacioppo, J.T., Berntson, G.G., Larsen, J.T., Poehlmann,K.M. and Ito, T.A. The psychophysiology of emotion. In Handbook of Emotions. Lewis, M. and HavilandJones, J.M.,Eds. Guilford Press, New York, 2000, 173-191. [10] Chiang, C.C. and Huang, C.J. A robust method for detecting arbitrarily tilted human faces in color images. Pattern Recognition Letters, 26, 16 (Dec. 2005), 2518-2536. [11] Costa, M., Dinsbach, W., Manstead, A.S.R. and Bitti, P.E.R. Social presence, embarrassment, and nonverbal behavior.Journal of Nonverbal Behavior, 25, 4 (Dec. 2001), 225-240. [12] Coulson, M. Attributing emotion to static body postures: Recognition accuracy, confusions, & viewpoint dependence.J. Nonverbal Behavior, 28, 2 (Jun. 2004), 117139.

12

Fa ci

USING THE 13

ABSTRACT While humans have had the innate ability to recognize and distinguish different faces for millions of years, computers are just now catching up. In this paper, we'll learn how computers are turning your face into computer code so it can be compared to thousands, if not millions, of other faces. We'll also look at how facial recognition software is being used in elections, criminal investigations and to secure your personal computer.

Facial recognition software falls into a larger group of technologies known as biometrics. Biometrics uses biological information to verify identity. The basic idea behind biometrics is that our bodies contain unique properties that can be used to distinguish us from others. Facial recognition methods may vary, but they generally involve a series of steps that serve to capture, analyze and compare your face to a database of stored images.

A Software company called Visionics developed Facial Recognition software called Faceit. The heart of this facial recognition system is the Local Feature Analysis (LFA) algorithm. This is the mathematical technique the system uses to encode faces. The system maps the face and creates a faceprint, a unique numerical code for that face. Once the system has stored a faceprint, it can compare it to the thousands or millions of faceprints stored in a database. Potential applications

even

include

ATM

and

check-cashing

security,

Security

Law

Enforcement & Security Surveillance and voter database for duplicates. This biometrics technology could also be used to secure your computer files. By mounting a Webcam to your computer and installing the facial recognition software, your face can become the password you use to get into your computer. By implementing this technology and the normal password security you are getting double security to your valuable data.

14

Introduction People have an amazing ability to recognize and remember thousands of faces. While humans have had the innate ability to recognize and distinguish different faces for millions of years, computers are just now catching up. In this paper, you'll learn how computers are turning your face into computer code so it can be compared to thousands, if not millions, of other faces. We'll also look at how facial recognition software is being used in elections, criminal investigations and to secure your personal computer.

The Face Your face is an important part of who you are and how people identify you. Imagine how hard it would be to recognize an individual if all faces looked the same. Except in the case of identical twins, the face is arguably a person's most unique physical characteristic. While humans have had the innate ability to recognize and distinguish different faces for millions of years, computers are just now catching up. Visionics, a company based in New Jersey, is one of many developers of facial recognition technology. The twist to its particular software, FaceIt, is that it can pick someone's face out of a crowd, extract that face from the rest of the scene and compare it to a database full of stored images. In order for this software to work, it has to know what a basic face looks like.

15

Facial recognition software can be used to find criminals in a crowd, turning a mass of people into a big line up. Facial recognition software is based on the ability to first recognize a face, which is a technological feat in itself, and then measure the various features of each face. If you look in the mirror, you can see that your face has certain distinguishable landmarks. These are the peaks and valleys that make up the different facial features. Visionics defines these landmarks as nodal points. There are about 80 nodal points on a human face. Here are a few of the nodal points that are measured by the software: •

Distance between eyes

•

Width of nose

•

Depth of eye sockets

•

Cheekbones

•

Jaw line

•

Chin

These nodal points are measured to create a numerical code, a string of numbers that represents the face in a database. This code is called a faceprint. Only 14 to 22 nodal points are needed for the FaceIt software to complete the recognition process. In the next section, we'll look at how the system goes about detecting, capturing and storing faces.

16

The Software Facial recognition software falls into a larger group of technologies known as biometrics. Biometrics uses biological information to verify identity. The basic idea behind biometrics is that our bodies contain unique properties that can be used to distinguish us from others. Besides facial recognition, biometric authentication methods also include: •

Fingerprint scan

•

Retina scan

•

Voice identification

Facial recognition methods may vary, but they generally involve a series of steps that serve to capture, analyze and compare your face to a database of stored images. Here is the basic process that is used by the FaceIt system to capture and compare images:

To identify someone, facial recognition software compares newly captured images to databases of stored images.

1. Detection - When the system is attached to a video surveillance system, the

recognition software searches the field of view of a video camera for faces. If there is a face in the view, it is detected within a fraction of a second. A multi-scale algorithm is used to search for faces in low resolution. (An algorithm is a program that provides a set of instructions to accomplish a specific task). The system switches to a high-resolution search only after a head-like shape is detected.

17

2. Alignment - Once a face is detected, the system determines the head's

position, size and pose. A face needs to be turned at least 35 degrees toward the camera for the system to register it. 3. Normalization -The image of the head is scaled and rotated so that it can be

registered and mapped into an appropriate size and pose. Normalization is performed regardless of the head's location and distance from the camera. Light does not impact the normalization process. 4. Representation - The system translates the facial data into a unique code. This

coding process allows for easier comparison of the newly acquired facial data to stored facial data. 5. Matching - The newly acquired facial data is compared to the stored data and

(ideally) linked to at least one stored facial representation. The heart of the FaceIt facial recognition system is the Local Feature Analysis (LFA) algorithm. This is the mathematical technique the system uses to encode faces. The system maps the face and creates a faceprint, a unique numerical code for that face. Once the system has stored a faceprint, it can compare it to the thousands or millions of faceprints stored in a database. Each faceprint is stored as an 84-byte file. The system can match multiple faceprints at a rate of 60 million per minute from memory or 15 million per minute from hard disk. As comparisons are made, the system assigns a value to the comparison using a scale of one to 10. If a score is above a predetermined threshold, a match is declared. The operator then views the two photos that have been declared a match to be certain that the computer is accurate. Facial recognition, like other forms of biometrics, is considered a technology that will have many uses in the near future. In the next section, we will look how it is being used right now.

Gotcha! The primary users of facial recognition software like FaceIt have been law enforcement agencies, which use the system to capture random faces in crowds.

18

These faces are compared to a database of criminal mug shots. In addition to law enforcement and security surveillance, facial recognition software has several other uses, including: •

Eliminating voter fraud

•

Check-cashing identity verification

•

Computer security

One of the most innovative uses of facial recognition is being employed by the Mexican government, which is using the technology to weed out duplicate voter registrations. To sway an election, people will register several times under different names so they can vote more than once. Conventional methods have not been very successful at catching these people. Using the facial recognition technology, officials can search through facial images in the voter database for duplicates at the time of registration. New images are compared to the records already on file to catch those who attempt to register under aliases. Potential applications even include ATM and check-

cashing

security. The software is able to quickly verify a customer's face. After the user consents, the ATM or

check-

cashing kiosk captures a digital photo of the customer.

The

facial recognition software then generates a faceprint of

the

photograph to protect customers against identity theft

and

fraudulent

transactions.

By

using

facial

recognition

software, there's no need for a picture ID, bank card or

personal

identification

identity.

number

(PIN)

to

verify

a

customer's

Many people who don't use banks use check-cashing machines. Facial recognition could eliminate possible criminal activity. This biometric technology could also be used

to

secure

your

computer

files.

By

mounting a Webcam to your computer and installing the facial recognition software, your face can become the password you use to get into your computer. IBM has incorporated the technology into a screensaver for it’s A, T and

19

X series ThinkPad laptops. Webcam and Facial Recognition Software installed

Newly Captured Image Comparing newly captured Image Database Image

Facial recognition software can be used to lock your computer.

Conclusion With the following advantages and also some of the drawbacks, we conclude our paper on Facial Recognition using Biometrics. Potential applications are as follows: •

Eliminating voter fraud

•

Security law enforcement and Security surveillance

• •

ATM and Check-cashing identity verification Computer security While facial recognition can be used to protect your private information, it can just as

easily be used to invade your privacy by taking you picture when you are entirely unaware of the camera. As with many developing technologies, the incredible potential of facial recognition comes with drawbacks. But if we add both the facial recognition and the normal password security we can have an added Double Security which is more reliable than one shield security, Just same as the quote “Two heads are better than one”.

20

MOBILE COMPUTING

SRKR ENGINEERING COLLEGE BHIMAVARAM. PRESENTED BY:

P.NARESH Regd.no:660751045 3rd year CSE

[email protected]

A.ANIL KUMAR Regd.no:660751009 3rd year CSE

[email protected]

21

ABSTRACT Mobile Computing:

A technology that allows transmission of data, via a

computer without having to be a connected to a fixed physical link. Mobile Computing and Communications is a major part of wireless communication technology. Mobile communication today is a de facto standard by itself. It commands the single largest share of the Global wireless technologies in the market. Mobile communications popularity grew many folds over the past few years and is still growing to a greater extent. Through WAP development of Mobile Computing Applications is becoming easy and affective.

It has also become a

foundation for many wireless LAN applications.

22

MOBILE COMPUTING INTRODUCTION

What will computers look like in ten years, in the next country? No wholly accurate prediction can be made, but as a general feature, most computers will certainly be portable. How will users access networks with the help of computers or other communication devices? An ever-increasing number without any wires, i.e., wireless. How will people spend much of their time at work, during vacation? Many people will be mobile already one of the key characteristics of today’s society. Think, for example, of an aircraft with 800 seats.

Modern aircraft already offer

limited network access to passengers, and aircraft of the next generation will offer easy Internet access.

In this scenario, a mobile network moving at high sped

above ground with a wireless link will be the only means of transporting data from passengers. There are two kinds of mobility: user mobility and device portability. User mobility refers to a user who has access to the same or similar telecommunication services at different places, i.e., the user can be mobile, and the services will follow him or her. With device portability the communication device moves (with or without a user). Many mechanisms in the network and inside the device have to make sure that communication is still possible while it is moving.

APPLICATIONS 1. Vehicles: Tomorrow’s cars will comprise many wireless communication systems and mobility aware applications.

Music, news, road conditions, weather reports, and

other broadcast information are received via digital audio broadcasting (DAB) with 1.5Mbits/s.

For

personal

communication,

a

global

system

for

mobile

communications (GSM) phone might be available. Networks with a fixed infrastructure like cellular phones (GSM, UMTS) will be interconnected with trucked radio systems (TETRA) and wireless LANs (WLAN). Additionally, satellite communication links can be used.

23

2. Business: Today’s typical traveling salesman needs instant access to the company’s database: to ensure that the files on his or her laptop reflect the actual state etc. MOBILE AND WIRELESS DEVICES

Sensor: A very simple wireless device is represented by a sensor transmitting state information. door.

An example for such a sensor could be a switch sensing the office

If the door is closed, the switch transmits this state to the mobile phone

inside the office and the mobile phone will not accept incoming calls. Thus, without user interaction the semantics of a closed door is applied to phone calls.

Pager: Mobile Phones: Personal digital assistant:

Mobile world meets cyberspace Mobile Internet is all about Internet access from mobile devices. Well, it’s true, but the ground realities are different. No doubt Internet has grown fast, well really fast! But mobile Internet is poised to grow even faster. The fundamental difference lies in the fact that whereas academics and scientists started the Internet, the force behind mobile Internet access is the cash-rich mobile phone industry. On the equipment side, the wireless devices represent the ultimate constrained computing device with: Less powerful CPUs, less memory (ROM and RAM), restricted power consumption The Wireless Application Protocol is the de-facto world standard for the presentation and delivery of wireless information and telephony services on mobile phones and other wireless terminals..

24

Wireless Application Protocol – WAP Three are three essential product components that you need to extend your host applications and data to WAP-enabled devices. These three components are: 1. WAP Micro browser – residing in the client handheld device 2. WAP Gateway – typically on wireless ISP’s network infrastructure 3. WAP Server - residing either on ISP’s infrastructure or on end user organization’s infrastructure

WAP Micro-browser : A WAP micro-browser is client software designed to overcome challenges of mobile handheld devices that enable wireless access to services such as Internet information in combination with a suitable network server Lots of WAP browsers and emulators are available free of cost which can be used to test your WAP pages. Many of these browsers and emulators are specific to mobile devices. WAP emulators can be used to see how your site will look like on specific phones. As these images show, the same thing can look different on different mobile phones. So, the problems that web developer faces with the desktop browsers (Netscape/I explorer) is present here also. So, make sure you test your code on different mobile phones (or simulators)

(Circuit Switched Data, around 9.6 kbps data rate)

25

Source: WAP for web developers, anywhereyougo.com A WAP server is simply a combined web server and WAP gateway. WAP devices do not use SSL. Instead they use WTLS. Most existing web servers should be able to support WAP content as well. Some new MIME types need to be added to your web server to enable it support WAP content. MIME stands for Multipurpose Internet Mail Extension.

Wireless Application Protocol - WAP WAP Communication Protocol & its Components The WAP Protocols cover both the application (WAE), and the underlying transport layers (WSP and WTP, WTLS, and WDP). WML and WML Script are collectively known as WAE, the Wireless Application Environment. As described earlier the 'bearer' level of WAP depends on the type of mobile network. It could be CSD, SMS, CDMA, or any of a large number of possible data carriers. Whichever bearer your target client is using, the development above remains the same. Although it’s not absolutely essential for a developer to know the details of the WAP communication protocols, a brief understanding of the various protocols involved, their significance and the capabilities can help a lot while looking for specific solutions.

WAE WML and WMLScript are collectively known as WAE, the Wireless Application Environment

WML WML is the WAP equivalent to HTML. It is a markup language based on XML (extensible Markup Language). The WAE specification defines the syntax, variables, and elements used in a valid WML file.

WBMP WBMP stands for Wireless Bitmap. It is the default picture format for WAP. The current version of WBMP is called type 0. As a thumb rule, a WBMP should not be wider than 96 pixels and higher than 48 pixels (at 72 dots per inch). There is also plug-ins available for Paint shop, Photoshop and Gimp, which let you save WBMP files with these programs.

26

•

Teraflops online converter

•

pic2wbmp

•

WAP Pictus

•

WAP Draw

•

WBMPconv & UnWired plug-in for Photoshop/PaintShop

WTLS the Security layer protocol in the WAP architecture is called the Wireless Transport Layer

Security,

WTLS.

WTLS

provides

an

interface

for

managing,

secure

connections. The differences arise due to specific requirements of the WTLS protocol because of the constraints presented by the mobile data systems. •

Long round-trip times.

•

Memory limitations of mobile devices

•

The low bandwidth (most of the bearers)

•

The limited processing power of mobile devices

•

The restrictions on exporting and using cryptography

WDP WTP The Transport layer protocol in the WAP architecture consists of the Wireless Transaction Protocol (WTP) and the Wireless Datagram Protocol (WDP). The WDP protocol operates above the data capable bearer services supported by multiple network types. As a general datagram service, WDP offers a consistent service to the upper layer protocol (Security, Transaction and Session) of WAP and communicate transparently over one of the available bearer services. Source: WAP- WDP Specifications

WAP: In Internet a WWW client requests a resource stored on a web server by identifying it using a unique URL, that is, a text string constituting an address to that resource. Standard communication protocols, like HTTP and Transmission Control Protocol/Internet Protocol (TCP/IP) manage these requests and transfer of data between the two ends. The content is transferred can be either static or

27

dynamic.

The strength of WAP (some call it the problem with WAP) lies on the fact that it very closely resembles the Internet model. In order to accommodate wireless access to the information space offered by the WWW, WAP is based on well-known Internet technology that has been optimized to meet the constraints of a wireless environment. Corresponding to HTML, WAP specifies a markup language adapted to the constraints of low bandwidth available with the usual mobile data bearers and the limited display capabilities of mobile devices - the Wireless Markup Language (WML). WML offers a navigation model designed for devices with small displays and limited input facilities.

28

Future Outlook For WAP: The point brought about by many analysts against WAP is that with the emergence of next generations networks (including GPRS), as the data capabilities of these networks evolve, it will make possible the delivery of full-motion video images and high-fidelity sound over mobile networks. Service delivers information at a speed of 9,600 bits of information a second. With GPRS the speed will rise to 100,000. Mobile commerce is one such application that can open up lots of opportunities for WAP. By 2010, there could be more than 1500m mobile commerce users. Mcommerce is emerging more rapidly in Europe and in Asia, where mobile services are relatively advanced, than in the US where mobile telephony has only just begun to take off. By allowing mobile to be in always connected state GPRS (or other services like CDPD) will bring Internet more closely to the mobile.

29

WAP Applications One of the most significant advantages of Internet access from mobile rather that your PC is the ability to instantly identify users geographic location. Some of the interesting applications of WAP (already existing or being worked on) are: •

Computer Sciences Corporation (CSC) and Nokia are working with a Finnish fashion retailer who plans to send clothing offers direct to mobile telephones using a combination of cursors.

•

In Finland, children already play new versions of competitive games such as "Battleships", via the cellular networks. In the music world, Virgin Mobile in the UK offers to download the latest pop hits to customers in a daily offering.

•

Nokia says applications that will benefit from WAP include customer care and provisioning, message notification and call management, e-mail, mapping and location services, weather and traffic alerts, sports and financial services, address book and directory services and corporate intranet applications.

WIRELESS LAN Wireless LAN technology constitutes a fast-growing market introducing the flexibility of wireless access into office, home, or production environments. WLANs are typically restricted in their diameter to buildings, a campus, single rooms etc. And are operated by individuals, not by large-scale network providers. The global goal of WLANs is to replace office cabling and, additionally, to introduce a higher flexibility for ad hoc communication in, e.g. Group meetings.

Some advantages of WLANs are: Flexibility: Planning: Only wireless ad hoc networks allow for communication without previous planning, any wired network needs wiring plans.

Design: Only wireless networks allow for the design of small, independent devices which can for example be put into a pocket.

30

Robustness: Wireless networks can survive disasters.

Some Disadvantages of WLANs:Quality of Service: WLANs typically offer lower quality than their wired counterparts.

Cost: While, e.g., high-speed Ethernet adapters are in the range of some 10 E, wireless LAN adapters, e.g., as PC-Card, still cost some 100 E.

Proprietary Solutions: Restrictions: Safety and Security: Mobile Network Layer This topic introduces protocols and mechanisms developed for the network layer to support mobility.

The most prominent example is Mobile IP, which adds

mobility support to the Internet network layer protocol IP. While systems like GSM have been designed with mobility in mind from the very beginning, the Internet started at a time when no-one had a concept of mobile computers. Another kind of mobility, rather portability of equipment, is supported by DHCP. In former times computers did not change their location often. Today, due to laptops or notebooks,

MOBILE IP The following gives an overview of Mobile IP, the extensions needed for the Internet to support the mobility of hosts. The following requires some familiarity with Internet protocols especially IP.

Goals, assumptions, and requirements: The Internet is the network for global data communication with hundreds of millions

31

of users. So why not simply use a mobile computer in the Internet? The reason is quite simple: you will not receive a single packet as soon as you leave your home network, i.e., the network your computer is configured for, and reconnect your computer (wireless or wired) at another place. The reason for this is quite simple if you consider routing mechanisms in the Internet.

A host

sends an IP packet with the header containing a destination address besides other fields. The destination address not only determines the receiver of the packet, but also the physical subnet of the receiver.

Quick ‘Solutions’: One might think of a quick solution to this problem by assigning the computer a new, topologically correct IP address.

So moving to a new location

would also mean assigning a new address. Now the problem is that nobody knows of this new address. It is almost impossible to find a (mobile) host in the Internet which has just changed its address.

Especially the domain name system (DNS)

need some time before it updates its internal tables necessary for the mapping of a logical name to an IP address.

This approach does not work if the mobile node

moves quite often. Furthermore, there is a severe problem with higher layer protocols like TCP that rely on IP addresses.

Changing the IP address while still having a TCP

connection open means breaking the connection.

A TCP connection can be

identified by the tuple (source IP address, source port, destination IP address, destination port), also known as a socket.

Requirements: •

Compatibility: A new standard cannot require changes for applications or network protocols already in use.

•

Transparency:

Mobility should remain ‘invisible’ for many higher layer

protocols and applications.

Besides maybe noticing a lower bandwidth and

some interruption in service, higher layers should continue to work even if the mobile computer changed its point of attachment to the network. •

Scalability and efficiency: Introducing a new mechanism into the Internet must not jeopardize the efficiency of the network. Enhancing IP for mobility must not generate many new messages flooding the whole network.

32

•

Security: Mobility poses many security problems. A minimum requirement is the authentication of all messages related to the management of Mobile IP.

CONCLUSION Mobile Computing and Communications is useful for wireless Networks. The study of different versions will give differences between Mobile Computing and Communications, Access Control, Security etc., the traditional mobile phone only had a simple black and white text display and could send / receive voice or short messages. Today, however, mobile phones migrate more and more toward PDAs. Mobile phones with full color graphic display, on the internet browser are available.

BIBLIOGRAPHY 1. Mobile Communications book by JOHEN SCHELLER. 2. Web Site from MobileComputing.Com

33

Rajeev Gandhi Memorial College of Engineering and Technology. TOPIC: DATA MINING AND WARE HOUSING. J.DHARANI KUMAR, II M.C.A, M.C.A,

P.N.SATISH KUMAR, II

06091F0007, 06091F0036, R.G.M.C.E.T, R.G.M.C.E.T, Nandyal. Nandyal. [email protected] p.n.satishkumar@gmail. com

Cell: 9441422114. Cell: 9704268488

ABSTRACT: Generally, data mining is the process of analyzing data from different perspectives And summarizing it into useful information - information that can be used to

34

increaseRevenue, cuts costs, or both. Data mining software is one of a number of analytical tools for Analyzing data. It allows Users to analyze data from many different dimensions or angles, Technically, data mining is the Process of finding correlations or patterns among dozens of Fields in large relational Databases. Although data mining is a relatively new term, the Technology is not. The objective of this paper is to provide full fledged information about the process Of data mining, the steps to process the mining etc., it also provides the more advantageous Techniques like data cleaning, integration etc., and all schemas for effective process and Mining.

INTRODUCTION: Data mining is the task of discovering interesting patterns from large amounts of Data, where the data can be stored in data bases, data ware houses, or other information Repositories. It is a young interdisciplinary field, drawing from areas such as database Systems, data ware housing, Statistics, machine learning, data visualization, information Retrieval, and high performance Computing. A knowledge discovery process includes data cleaning, data integration, and data Selection, data Transformation, data mining, pattern evaluation, and knowledge presentation. A Warehouse is a Repository for long-term storage of data from multiple sources organized To as facilitate management Decision making .The data are stored under a unified schema And are typically summarized. Data Ware house systems provide some data analysis Capabilities collectively referred to as OLAP (on-Line Analytical Processing). Figure (1): Architecture of typical data mining system

35

Data mining-on what kind of data? Data mining should be acceptable to any kind of information repository. This Include relational data bases, data ware houses, transactional databases, advansed Database systems Include object-oriented and objectrelational data bases, and specific Application oriented data bases Such as spatial databases, text databases, and multimedia Data Bases. The challenges and techniques of mining may differ for each repository systems.

DATA PREPROCESSING: data.

We have to preprocess the data in order to help improve the quality of

Today’s real-World data bases are highly suspect able to noisy, missing, and inconsistent Data due to their typically huge size and their likely origin from multiple heterogeneous Sources. Low quality will lead to low quality mining results. To avoid these anomalies we have the following techniques.

36

DATA CLEANING – Remove noise and correct inconsistencies in data. DATA INTEGRATION Merges data from multiple sources, into coherent data sore. DATA TRANSFERMATING-Connect the data into appropriate forms for mining. DATA REDUCTION – Reduces the data size by aggregate elemenatingredundanc.

The above techniques are not mutually exclusive, they may work together. “Data processing techniques when applied before mining can substantially Improve the Overall the quality of the data”. Patterns mined and/or the time required for Actual mining. Descriptive data summarization provides the analytical foundation for data Processing. The basic Statistical measures for data summarization are mean, weighted mean, Median and mode etc., are Used to measuring central tendency of data.

OLAP TECHNOLOGY: Data ware houses provide On-line analytical process (OLAP) tools for Interactive Analysis of multidimensional data of varied granularities, which facilitates data Generalization and Data mining. Many other data mining functions such as association, Classification, and prediction and Clustering can be integrated with OLAP operations to Enhance interactive mining of knowledge at multiple levels of abstraction.

MULTIDIMENSION DATAMODEL: Data ware houses and OLAP tools are based on multidimensional data model. This Model views data to be modeled and viewed in multiple dimensions. It is identified by Dimensions and facts. “Dimensions are the perspective or entities with respect to which an organization Wants to keep records”. Each dimension may have a table associated with it, called dimension table. “The facts are the quantities by which we want to analyze relationships

37

between Dimensions”. Fact table contains, or measures as well as keys to each of the relate Dimension tables.

3-d CUBES: We usually think of cubes as 3-d geometric structures, in data warehousing the Data cube is n-dimensional. The example of 3-d cube is shown in the below figure (2). Figure (2): Example of 3-d cube.

110

60

25

40

90

50

30

Arizona

70

55

60

35

Washington

75

85

45

45

12/31/2003 …..

65

45

85

60

1/2/2003 Time 1/1/2003

Location

80

Utah

4-d:

California

Colorado

Soda

Diet Orange Lime soda soda soda Product

If we want to add or view additional data we can go for 4-d approach. We can think 4-d Cube as a series of 3-d cubes. The data cube is a metaphor for data storage.

STARS, SNOW FLAKES AND FACT CONSTELLATIONS: 

Star schema: (1) a

The most commonly used model. A star schema contains

Large Central table (fact table) containing the bulk of data with no

redundancy (2) a Set of smaller Attendant tables (dimension tables) one for each dimension.

38

Snow flake schema: The snowflake schema is a variant of the star schema where Some Dimension tables are normalized, thereby further splitting the data into Additional tables the major difference between snowflake and star schema is that the Dimension tables of Snowflake model are kept in normalized form to avoid Redundancies.

Such tables can save space

.



However snowflake schema may necessitate more joins.



Fact constellation:

Sophisticated applications may require multiple fact

tables to Share Dimension tables. 

This kind of schema is called galaxy schema or fact constellation.

How to define multidimensional schema? 

DMQL (Data Mining query language) contains primitives for defining data Warehouses and data marts



define cube( cube_name) [ ( Dimension list) ] : (measure list)



define dimension ( dimension_name) as((attribute_or_subdimension_list)) OLAP operations in a Multi Dimensional Data Model: Roll Up, Drill Drown,

Slice And Dice, And Pivot.

The Process Of Data Warehouse Design:  Choose a business process to model  Choose the grain of the business process.  Choose the dimensions that will apply to each fact table record.  Choose the measures that will populate each fact table record  The Spiral Method involves the rapid generation of increasingly functional systems, With Short intervals between successive releases.

39



This is considered a good choice for data warehouse development, especially for data Marts, because the turnaround time is short, modifications can be done quickly and New designs and technologies can be adapted in a timely manner.

Three-Tier Data Warehouse Architecture:  The bottom tier is a warehouse database server that is almost always a relational Database System. The middle tier is an OLAP server that is typically implemented Using either ROLAP or MOLAP. The top tier is a client, which contains query and reporting tools, Analysis tools, and/or data mining tools (e.g., trend analysis, prediction…).

Data Warehouse Implementation: 

Efficient computation of data cubes, Indexing of OLAP data, Efficient processing of OLAP Queries, Metadata Repository, Data warehouse Back-End tools and utilities.

MOLAP TECHNOLOGY: 

Partition the array into chunks. A chunk is a sub cube that is small enough to fit intoThe Memory available for cube computation. Chunking is a method for dividing an N-dimensional chunks, where each chunk is stored as an object on disk.

 Compute aggregates by visiting (i.e.accesing the values at) cube cells. The order in Which Cells are visited can be optimized so as to minimize the number of times that Each cell must be revisited, thereby reducing memory access and storage costs.

40

Metadata Repository: 

A description of the structure of the data warehouse, which includes the warehouse

Schema,

View,

dimensions,

hierarchies,

definitions, as well as data Mart locations

and

derived

data

and contents. Operational

metadata, which include data lineage, Currency of data, and monitoring information. The algorithms used for Summarization, which include measure and Dimension definition algorithms, data on Granularity, partitions, subject areas, aggregation, Summarization, and predefined Queries and reports. The mapping from the operational Environment to the data warehouse, This includes source databases and their contents, Gateway descriptions, data partitions, Data extraction, cleaning, transformation rules and Defaults, data refresh and purging rules, And security. Data related to system performance, Which include indices and profiles that improve data access and retrieval? Performance, in

Addition to rules for the timing and scheduling of refresh, update,

and Replication cycles. Business metadata, which include business terms and definitions, data Ownership information and charging policies.

Data Warehouse Back-End Tools And Utilities: 

Data Extraction, which typically gathers data from multiple, heterogeneous, and External Sources.

 Data Cleaning, which detects errors in the data and rectifies them when possible  Data Transformation, which converts data from legacy or host format to warehouse Format  Load, which sorts, summarizes, consolidates, computes views, checks integrity, and Builds Indices and partitions

41

 Refresh, which propagates the updates from the data sources to the warehouse

DESCISSION SUPPORT TOOLS-OVER VIEW:

Decision support tools DIRECT QUERY

Reporting Tools Crystal reports

Merge Clean Summarize

OLA P

Mining tools

Essbase

Intelligent Miner

Data warehouse

GI Detailed S transactional dat Operational data data a Bombay Delhi Calcutta branch branch branch Oracle IMS

Relational DBMS+ E.g. Redbrick

Cens us data SAS

Conclusion: •

The value of warehousing and mining in effective decision making based on concrete Evidence from old data

•

Challenges of heterogeneity and scale in warehouse construction and maintenance

•

Grades

of

data

analysis

tools:

straight

querying,

reporting

tools,

multidimensional Analysis and mining.

42

Before going to mine the data we have to pre process the data to prevent anomalies Such as noise etc..,

BIBLIOGRAPHY 1) Data Mining Concepts and techniques by Jiawei Han and Micheline Kamber, ELSEVIER SEERIES second edition. 2) Informatica Power Center 8.1.1. 3) www.anderson.ucla.edu (url.)

43

ARCHITECTURE, CHALLENGES AND RESEARCH ISSUES ON MOBILE COMPUTING

BY

H.SUSHMA III CSE G.PULLA REDDY ENGINNERING COLLEGE KURNOOL Email: [email protected]

N.KAUSER JAHAN III CSE G.PULLA REDDY ENGINNERING COLLEGE KURNOOL Email: [email protected]

44

Abstract With the advent of the Internet and the plurality and variety of fancy applications it brought with it, the demand for more advanced services on cellular phones increasingly becoming urgent. Unfortunately, so far the introduction of new enabling technologies did not succeed in boosting new services. The adoption of Internet services has shown to be more difficult due to the difference between the Internet and the mobile telecommunication system. The goal of this paper is to examine the characteristics of the mobile system and to clarify the constraints that are imposed on existing mobile services.

The paper will also investigate

successively the enabling technologies and the improvements they brought. Most importantly, the paper will identify their limitations and capture the fundamental requirements for future mobile service architectures namely openness, separation of service logic and content, multi-domain services, personalization, Personal Area Network (PAN)-based services and collaborative services. The paper also explains the analysis of current mobile service architecture such as voice communication; supplementary services with intelligent network, enabling services on SIM with SIM application tool kit, text services with short message service, internet services with WAP and dynamic applications on mobile phones with J2ME. Further our paper gives information on challenges of mobile Computing

which

Heterogeneous Overlays,

includes

harsh

communications,

connections,

bandwidth

and

networks. Under research issues seamless connectivity over multiple

scalable mobile processing, wireless communications, mobility portability

and

are discussed.

1. Introduction With digitalization the difference between telecommunication and computer net-working is fading and the same technologies are used in both fields. However, the convergence does not progress as rapidly as expected. Moving applications and services from one field to the other has proven to be very difficult or in many cases impossible. The explanation is that although the technologies in use are rather similar there are crucial differences in architecture and concepts. The paper starts with a study of how mobile services are implemented in mobile telecommunication

45

systems and an identification of their limitations so as to meet the needs of the future.

2. Analysis of current mobile service architectures 2.1 Voice communication As indicated by its name, the objective of mobile telecommunications systems is to

provide

communication

between

mobile

distant

persons.

systems only

supported direct voice communication or telephony between two

participants, but

supplementary services like call forwarding, barring and voice mail

were added later

on.

2.2 Supplementary services with intelligent network take

long

like call

forwarding, barring, voice

an IN

(Intelligent Network [1]) Service Control Point (SCP) is

mobile

network to allow the implementation of supplementary services

These

:It does not

time before there is a need for more advanced call control ser-vices mail, premium call, etc. As shown in Figure 3 introduced in the

2.3 Enabling services on the SIM with SIM Application Toolkit (SAT) The telecom operators want to have other services than telephony and its derivatives and turn to the

SIM, which are their property. Unfortunately,

although the SIM is a smart card having both processing and

storage

capabilities necessary for new services. The SIM is supposed to be the slave executing orders

from its master, the ME. To remedy this, the SIM Application Tool-kit (SAT)

[2] is

introduced to allow

the

input and output units. With SAT it is possible to

the SIM

but there are many restrictions. First SAT applications should be small in

applications/services residing on the SIM to control develop

applications

on

size. Secondly, operators who are reluctant to open the access due to security control

the installation

of applications on the SIM.

2.4 Text services with Short Message Service (SMS) : responsible to

store and forward messages to and from mobile phone

(see

Figure 3). In the illustration, components

in the

ME advanced SMS services are implemented by perlscripets.

of

SMS-C is

used for SMS are the client (C) Provisioning

SMS services requires installation of the above-mentioned application

46

on an SMS

Gateway the system running the SMS Gateway to act as an SMSC itself (e.g.

a PC

using a radio modem

specific

service (the protocol)

and the additional identifiers and parameters for a

2.5 Internet access with WAP: Wireless

Application Protocol (WAP) [5]

was to

provide

access to the WWW on handheld terminals. A micro browser

installed

Internet and the mobile network to convert

binary

protocols as shown in Figure 3.. One restriction of the technology is

is not

possible to access ordinary web pages using a WAP browser.

Internet protocols to Wireless that it

2.6 Dynamic applications on mobile phones with J2ME (CLDC/MIDP):

Unlike a computer, the functionality of the mobile phones is defined at

manufacture time and it is not

possible to install new applications. With

introduction of the J2ME CLDC/MIDP vast amount of applications,

sophisticated

called MIDLETS can be found on the Internet. With J2ME, it is possible to develop

dynamic standalone applications.

3. Advanced Architecture This section aims at identifying and elucidating the advanced pieces and hence

contributes to the definition of advanced architecture.

3.1 Separation of service content and logic Mobility is the ultimate requirement for mobile services. The mobility

47

properties of a

service are dependent on the architecture and particularly on the

location of the

components, service logic and service content, makes the analysis

easier. In early

mobile telecom services the service logic was embedded in the

dedicated hardware

components. This has been a hindrance for development of

flexible services; these

services will by default not be accessible from outside an

operator domain. To enhance the mobility of ser-vices, it is necessary to decouple the service logic from the system

components.

3.2 Multi-domain services By using this service we cannot only access all services provided by the

network but also many users can work at the same time. Mobile

services will be provided as distributed services where the logics residing in different

places will cooperate in delivering the end user service.

48

3.3 PAN-based Services:

Nowadays, each individual is using several

devices like mobile phones, PDA’s, digital camera, GPS, etc. With the emergence of wireless short-range technologies like Bluetooth, WLAN and potentially, Personal Area Networks can be formed to allow

communication

betweendevices.

3.4CollaborativeServices:

With a multi-domain service, it will be possible

for people not only to collaborate across network boundaries, but also across terminal boundaries. It is also possible for several people to collaborate by exchanging information through several channels and devices simultaneously such as talking on the phones, showing picture on digital cameras, reading document on PDA’s.

4.Challenges of Mobile Computing:

49

Freedom from Collocation

50

• Harsh communications environment. The unfavorable Communication environment is coupled with Lower bandwidth/higher latency not good enough for videoconferencing or any other

process. It has higher error rates and more frequent disconnection. Its performance depends on density of nearby users but inherent scalability of cellular/frequency reuse architecture helps.

• Connection/Disconnection: Network failure is a common issue and therefore Autonomous operation is highly

desirable. Found it often Caching is a good idea, e.g., web cache.

• Low Bandwidth – Orders of magnitude differences between wide-area, in building wireless

• Variable Bandwidth – Applications adaptation to changing quality of connectivity

» High bandwidth, low latency: business as usual » High bandwidth, high latency: aggressive prefacing » Low bandwidth, high latency: asynchronous operation, use caches to hide

latency, Predict future references/trickle in, etc. etc.

• Heterogeneous Networks “Vertical Handoff” among collocated wireless networks

5.Research Issues • Seamless connectivity over multiple overlays – Implementing low latency handoffs – Exploiting movement tracking and geography – Performance characterization of channels – Authentication, security, privacy

• Scalable mobile processing – Hierarchical and distributed network management ,load balancing for

network

mgmt – Integration with local- & wide-area networked servers -Application support for adaptive connections

Wireless Communications – Quality of connectivity

and Bandwidth limitations

• Mobility Location transparency and

Location dependency

• Portability Power limitations, Display, processing and storage limitations

6. Conclusion This paper presents an analysis of the evolutionary path of mobile services, from

early

voice

communication

services

to

prospects

of

future

service

possibilities. It

is argued that increasing openness can help excel the future of

mobile services.

Each of the concepts discussed around mobile services in this paper

are on their own and of research and they must be further elaborated in separate studies.

Thus, the discussions in this paper are preliminary and do address only the

basic

structures and further works will be carried out.

7. References Gunnar Heine, GSM Networks: Protocols, Terminology and Implementation. http\\: www.iitd.ac.in J. B. Andersen, T. S. Rappaport, S. Yoshida, "Propagation Measurements and

Models

for

Magazine,

Wireless

Communications

Channels,"

IEEE

Communications

pp. 42-49 and H. Forman, J. Zahorjan, "The Challenges of Mobile

Computing," IEEE

Computer, V 27, N

Devineni Venkata Ramana & Dr. Hima Sekhar

MIC College of Technology Presented by…. A.Spandana (IIIrd year CSE) Email id: [email protected]

M.P.Priyadarshini (IIIrd CSE) Email id: [email protected]

ABSTRACT The growth of wireless networking has blurred the traditional boundaries between trusted and untrusted networks and shifted security priorities from the network perimeter to information security. The need to secure mobile information and control the wireless environment to prevent unauthorized access must be a priority for maintaining the integrity of corporate information and systems. But running a business from home using a home wireless local area network (WLAN) with your computer may lead to thievery of confidential information and hacker or virus penetration unless proper actions are taken. As WLANs send information back and forth over radio waves, someone with the right type of receiver in your immediate area could be picking up the transmission, thus acquiring

access

to

your

computer.

WIRELESS ATTACKS Wireless Deploying a wireless network does not require special expertise. If a department is eager to expand its network and it can’t or doesn’t want to wait for the normal IT process, it can expand the network itself cheaply and easily, just by plugging an Access Point into an Ethernet jack and by plugging a wireless card into a laptop. Attacks

Basic LAN environment

•

Surveillance

There are several approaches to locating a wireless network. The most basic method is a surveillance attack. You can use this technique on the spur of the moment, as it requires no special hardware or preparation. Most significantly, it is difficult, if not impossible, to detect. How is this type of attack launched? You simply observe the environment around you. •

War driving

The term war driving is borrowed from the 1980s phone hacking tactic known as war dialing. War dialing involves dialing all the phone numbers in a given sequence to search for modems. In fact, this method of finding modems is so effective that it's still in use today by many hackers and security professionals. Similarly, war driving, which is now in its infancy, will most likely be used for years to come both to hack and to help secure wireless networks. •

Client-to-client hacking

Clients exist on both wireless and wired networks. A client can range from anything such asa Network Attached Storage (NAS) device, to a printer, or even a server. Because the majority of consumer operating systems are Microsoft based, and since the majority of users do not know to how to secure their computers, there is plenty of room to play here. An attacker can connect to the laptop, upon which he could exploit any number of operating system vulnerabilities, thus gaining root access to the laptop. •

Rogue Access Point

Rogue access points are those connected to a network without planning or permission from the network administrator. For example, we know one administrator in Dallas who just did his first wireless security scan (war driving) on his eight-building office campus. To his surprise, he found over thirty access points. Worse, only four of them had authorization to be connected to the network. Needless to say, heads rolled.

Jamming(Denial of Service)

Denial-of-service (DoS) attacks are those that prevent the proper use of functions or services. Such attacks can also be extrapolated to wireless networks. •

Practical WEP cracking

"Cracking WEP," is fundamentally flawed, allowing you to crack it. This will thwart the casual drive-by hacker. It also enables another layer of legal protection that prohibits the cracking of transmitted, encrypted signals.

SECURING THE WLAN For WLANs, the first step in security hardening is to focus on the access point. Since the AP is the foundation of wireless LAN data transfer, you must ensure that it is part of the solution, instead of the problem.

•

Access Point based security •

WEP: Enabling a protection that is minimally effective, you can

eliminate 99% of your threat. Similar to a car lock, WEP will protect your network from passers-by; however, just as a dedicated thief will quickly bypass the lock by smashing a car window, a dedicated hacker will put forth the effort to crack WEP if it is the only thing between him and your network. •

MAC Filtering: Every device on a wireless network, by default, has

a unique address that's used to

identify one WNIC from another. This

address is called the MAC address. To find the MAC address of the network card the user only have to perform a few steps based on the operating system However, while this in theory is an excellent way to stop hackers from accessing your WLAN, there is a serious flaw in MAC filtering. The problem with MAC filtering is that MAC addresses can be spoofed by changing WNIC settings. •

Controlling Radiation zone: When a wireless network is active, it

broadcasts radio frequency (RF) signals. These signals are used to transmit the wireless data from an access point to the WNIC and back

again. The same signal is also used in ad-hoc networks, or even between PDAs with 802.11 WNICs. By using antenna management techniques, you can control the range of your WLAN. In high-rise buildings or apartment complexes, this can be a serious issue. Interference—and nosy neighbors —can quickly become a problem. By removing one antenna, reducing the output, and adjusting the position of the antenna, you can effectively keep the signal within a tight range •

Defensive Security Through a DMZ: A DMZ, or demilitarized zone,

is a concept of protection. A DMZ typically defines where you place servers that access the Internet. In other words, a Web server or mail server is often set up in a DMZ. This allows any Internet user to access the allocated resources on the server, but if the server becomes compromised, a hacker will not be able to use the "owned" computer to search out the rest of the network. Technically, a DMZ is actually its own little network, separate from the internal network, and separate from the Internet. However, while this type of protection can help protect internal resources, it will not protect the wireless network users. Therefore, the DMZ should be just one part of your wireless security plan.

• Third party security methods •

Firewalls:

Firewall separates the wireless users from the internal

users. A firewall can do much to eliminate security threats. Depending on how it is set up and what types of policies are used, a firewall can effectively block all incoming requests that are not authorized. This creates a physical barrier to crackers who might have control over the wireless network and are trying to breach the internal network..

•

VPN’s:

VPNs

create

encrypted

channels

to

protect

private

communication over existing public networks. A VPN enables you to establish a secure, encrypted network within a hostile, public network such as the Internet. VPNs provide several benefits, including the following: •

Facilitate secure and easy inter-office communication

•

Provide inexpensive network access for mobile employees

•

Provide full network access for telecommuters

VPNs provide secure, encrypted communication in two ways: User-to-Network (Remote-Access Model) — In this configuration, remote

•

clients can connect through a public network such as the Internet. By using a VPN, the remote client can become part of the company network. This configuration effectively replaces the remote dial-in or authenticated firewall access model. Network-to-Network (Site-to-Site Model) — In this configuration, one

•

branch office network can connect through a public network such as the Internet to another branch office network. This configuration eliminates the need for an expensive wide-area network (WAN). Thus, VPNs are secure communication solutions that take advantage of public networks to lower your costs. However, VPNs have their share of problems.

•

Radius: Remote Authentication Dial-In User Service (RADIUS) is a

protocol that is responsible for authenticating remote connections made to a system, providing authorization to network resources, and logging for accountability purposes. Although the protocol was developed to help remote modem users securely connect to and authenticate with corporate networks, it has now evolved to the point where it can also be used in VPNs and WLANs to control almost every aspect of a user's connection. There are several brands of RADIUS servers available. One of the more popular is Funk's SteelBelted Radius server, which is often deployed with Lucent WLAN setups. •

Funk’s Steel Belted Radius

Funk’s product is a functional software package that provides a central point of administration for all remote users, regardless of how they connect. ."Steel-Belted Radius is an award-winning RADIUS/AAA server that lets you centrally manage all your remote and wireless LAN (WLAN) users and equipment, and enhance the security of your network." Steel-Belted Radius earns a second look because it provides extra security for WLAN users by increasing the level of security and access by working with existing access points to ensure only authorized users are allowed access. Features of Funk's Steel-Belted Radius:

• Central User Administration: Steel-Belted Radius manages remote and

WLAN users by allowing authentication procedures to be performed from one database. This relieves you of the need to administer separate authentication databases for each network access or WLAN access point device on your LAN. Steel-Belted Radius performs three main functions: •

Authentication— Validates any remote or WLAN user's username and password against a central security database to ensure that only individuals with valid credentials will be granted network access.

•

Authorization— For each new connection, provides information to the remote access or WLAN access point device, such as what IP address to use, session time-limit information, or which type of tunnel to set up.

•

Accounting— Logs all remote and WLAN connections, including usernames and connection duration, for tracking and billing. •

Central

Hardware

administration:

Steel-Belted

Radius

can

manage the connections of all your remote and wireless users. This includes the following: •

Dial-up users who connect via remote access servers from 3Com, Cisco, Lucent, Nortel, and others.

•

Internet users who connect via firewalls from Check Point, Cisco, and others.

•

Tunnel/VPN users who connect via routers from 3Com, Microsoft, Nortel, Red Creek, V-One, and others.

•

Remote users who connect via outsourced remote access services from ISPs and other service providers.

•

Wireless LAN users who connect via access points from Cisco, 3Com, Avaya, Ericsson, Nokia and others.

•

Users of any other device that supports the RADIUS protocols.

Moreover, Steel-Belted Radius supports a heterogeneous network, interfacing with remote and wireless access equipment from different vendors simultaneously •

Authentication methods: Steel-Belted Radius not only works with

a wide variety of remote and wireless access equipment, but it also makes it

possible

to

authenticate

remote

and

WLAN

users

according

to

any

authentication method or combination of methods you choose. In addition to Steel-Belted Radius's native database of users and their passwords, Steel-Belted

Radius

supports

"pass-through"

authentication

to

information

contained in the Steel-Belted Radius can simultaneously authenticate many users. If you are combining authentication methods, you can even specify the order in which each is checked. The result is streamlined administration, as well as one-stop authentication

Securing Your Wireless LAN: Steel-Belted Radius play a pivotal role in securing their connections. Steel-Belted Radius provides additional security on a WLAN by •

Protecting against rogue access points. Steel-Belted Radius ignores communications from any access point that is not registered with it. This helps prevent network intrusion from illegally installed or used equipment.

•

Supporting time session limits, time-of-day restrictions, and other RADIUS attributes, which let you impose additional security constraints on WLAN usage.

Steel-Belted Radius also makes it possible to manage both wireless LAN and remote users from a single database and console, greatly reducing your administrative burden by eliminating the need for two separate authentication systems. • WLAN protection enhancement • TKIP: The Temporal Key Integrity Protocol (TKIP) is used to correct WEP

problems. TKIP uses RC4 as the encryption algorithm, but it removes the weak key problem and forces a new key to be generated every 10,000 packets or 10kb, depending on the source. TKIP is a stronger and more secure method of verifying the integrity of the data. Called the Message Integrity Check, this part of TKIP closes a hole that would enable a hacker to inject data into a packet so he can more easily deduce the streaming key used to encrypt the data.

• AES: Advanced Encryption Standard (AES) is a newer encryption method that was selected by the U.S. government to replace DES as their standard. It is quite strong, and is actually under review for the next version of the wireless 802.11 standard (802.11i). AES allows different sizes of keys, depending on need. The key size directly reflects the strength of the encryption, as well as the amount of processing required to encrypt and decipher the text.



3.4 x 1038 possible 128-bit keys



6.2 x 1057 possible 192-bit keys



1.1 x 1077 possible 256-bit keys Nevertheless, AES is destined to be the encryption method of all wireless

traffic. • SSL: Secure Sockets Layer is a protocol that uses RC4 to encrypt data

before it is sent over the Internet. This provides a layer of security to any sensitive data and has been incorporated into almost all facets of online communication. Everything from Web stores, online banking, Web-based email sites, and more use SSL to keep data secure. The reason why SSL is so important is because without encryption, anyone with access to the data pipeline can sniff and read the information as plaintext. By using a Web browser with SSL enabled, an end user can make a secure and encrypted connection to a WLAN authentication server without having to deal with cumbersome software. As most wireless users will be familiar with using secure Web sites, the integration of SSL will go unnoticed. Once the connection is made, the user account information can be passed securely and safely. • ID’s: Intrusion detection systems (IDSs) provide an additional level of

security for your wireless-enabled network. By adding wireless access to your network, you are dramatically increasing your risk of compromise. To counter this increased threat, you should also consider adding additional layers of security for a defense in depth. A firewall and VPN(“Virtual Private Networks") might no longer be enough. Fortunately, a properly configured IDS can satisfy your demand for extra security by notifying you of suspected attacks.

Log file monitors: The simplest of IDSs, log file

•

monitors, attempt to detect intrusions by parsing system event logs. This technology is limited in that it only detects logged events, which attackers can easily alter. In addition, such a system will miss low-level system events, because event logging is a relatively high-level operation.

•

Integrity Monitors: An integrity monitor watches

key system structures for change Although limited, integrity monitors can add an additional layer of protection to other forms of intrusion detection. The most popular integrity monitor is Tripwire. Signature Scanners: the majority of IDSs attempt

•

to detect attacks based on a database of known attack signatures. When a hacker attempts a known exploit, the IDS attempts to match the exploit against its database.

WIRELESS PUBLIC KEY INFRASTRUCTURE The encryption and decryption keys are different in public key cryptography. In public key encryption Each user has a pair of keys namely the public and private keys.Publickey encryption uses a one way function to scramble the data using the recipient’s public key and the recipient should in turn decrypt the data using this private key. •

Public key cryptography

In encryption applications, a tested and proven mathematical algorithm play a very important role The following are the most commonly used public key algorithms: Public key ring public key

private key Transmitted Ciphertext





plaintext input

Encryption Algorithm

Decryption Algorithm

plaintext output

Public key encryption

•

RSA: This algorithm is named after its three inventors: Ron Rivest,

Adi Shamir, and Leonard Adleman.It is cryptographically strong, and is based

on the difficulty of factoring large numbers.It is capable of both digital signature and key exchange operations. DSA: It is the digital signature algorithm invented by national

•

security agency of USA and is used for digital signature operations and not for data encryption. Its cryptographic strength is based on the difficulty of calculating discrete logarithms. Diffie-Hellman— This algorithm is named after its inventors Whitfield

•

Diffie and Martin Hellman. can be used for key exchange only. The cryptographic strength of Diffie-Hellman is based on the difficulty of calculating discrete logarithms in a finite field. DigitalSignatures:

•

The concept of digital signatures has evolved to

address such threats such as snoofing and tampering. •

One-Way Hash Algorithms: Digital signatures rely on a mathematical

function called a one-way hash. A hash utilizes a one-way (irreversible) mathematical function (a hash algorithm) to transform data into a fixedlength digest, known as the hash value. Each hash value is unique. Thus, authentication using the hash value is similar to fingerprinting. To verify the origin of data, a recipient can decrypt the original hash and compare it to a second hash generated from the received message. Two common one-way hash functions are MD5 and SHA-1. MD5 produces a 128-bit hash value, and is now considered less secure. SHA-1 produces a 160-bit hash value. In PKI, hashes are used to create digital signatures. CONCLUSION Today, most organizations deploying wireless LANs simply haven’t put enough effort into its security – it isn’t right, but it is true. Just like in the wired world, organizations only began to take Internet security seriously after there had been a series of highly visible and financially damaging hacker attacks. Only a similar series of public wireless disasters will catalyze the change needed for organizations to take wireless security more seriously. While there are a number of inherent security problems with the 802.11 technology, there are also many straightforward measures that can be taken to mitigate them. As with many new technologies, the best way to get started is to recognize the problems and make a commitment to address the ones that can

reasonably be solved in our environment Digital Certificates, and Cryptographic Modules are the fundamental building blocks of strong authentication and there is no way around that. You can make the best of it by leveraging the hefty investment for all your security needs. REFERENCES 1) www.gigapedia.org 2) www.findfreearticles.com

INTERNET SECURITY AGAINST HACKING SYSTEMS N. Narmada chowdary. R. Alekhya. 2/4 B.ECH C.S.E. V.R.SIDDHARTHA ENGINNEERING COLLEGE.

Vijayawada. Ph no:9490907741.

ABSTRACT The internet has been a wide usage in all the fields in the present competitive world. It is being used in the education, research, business and what not, in everything. But providing security for the users information or transactions or any other data in any of the field has become a paramount. This paper gives a vivid picture of “E-commerce” and the vulnerabilities they are facing in providing a secure system for the users. In other words, how the security attacks are made either by the hackers or the intruders, the ways how they attack and exploit to illegitimate means. This paper is an overview of the security and privacy concerns based on the experiences as developers of E-commerce. E-commerce is a business middleware that accelerates the development of any business transaction-oriented application, from the smallest retailer to the distributor, to the consumer (user). These transactions may apply b between manufacturers and distributors or suppliers. Here, the user needs to be assured with the privacy of his/her information. In this article, we focus on possible attack scenarios in an e-Commerce system and provide preventive strategies, including security features that one can implement. Here we present you the better ways of how to defend from the attacks and protect your personal data without depending on the network provider’s security with the help of personnel firewalls and honey pots.

INTRODUCTION E-Commerce refers to the exchange of goods and services over the Internet. All major retail brands have an online presence, and many brands have no associated bricks and mortar presence. However, e-Commerce also applies to business to

business transactions, for example, between manufacturers and suppliers or distributors. E-Commerce provides an integrated platform that runs both their customer facing online shopping sites, and their internal distributor or supplier portals as shown in Figure.

E-Commerce systems are relevant for the services industry. For example, online banking and brokerage services allow customers to retrieve bank statements online, transfer funds, pay credit card bills, apply for and receive approval for a new mortgage, buy and sell securities, and get financial guidance and information.

SECURITY OVERVI EWAND ITS FEATURES: A secure system accomplishes its task with no unintended side effects. Using the analogy of a house to represent the system, you decide to carve out a piece of your front door to give your pets' easy access to the outdoors. However, the hole is too large, giving access to burglars. You have created an unintended implication and therefore, an insecure system. While security features do not guarantee a secure system, they are necessary to build a secure system. Security features have four categories: •

Authentication: Verifies who you say you are. It enforces that you are the only one allowed to logon to your Internet banking account.

•

Authorization: Allows only you to manipulate your resources in specific ways. This prevents you from increasing the balance of your account or deleting a bill.

•

Encryption: Deals with information hiding. It ensures you cannot spy on others during Internet banking transactions.

•

Auditing: Keeps a record of operations. Merchants use auditing to prove that you bought specific merchandise.

The victims and the accused (the players): In a typical e-Commerce experience, a shopper proceeds to a Web site to browse a catalog and make a purchase. This simple activity illustrates the four major players in e-Commerce security. One player is the shopper who uses his browser to locate the site. The site is usually operated by a merchant, also a player, whose business is to sell merchandise to make a profit. As the merchant business is selling goods and services, not building software, he usually purchases most of the software to run his site from third-party software vendors. The software vendor is the last of the three legitimate players.

A threat is a possible attack against a system. It does not necessarily mean that the system is vulnerable to the attack. An attacker can threaten to throw eggs against your brick house, but it is harmless. Vulnerability is a weakness in the system, but it is not necessarily be known by the attacker. Vulnerabilities exist at entry and exit points in the system. In a house, the vulnerable points are the doors and windows.

Points the attacker can target As mentioned, the vulnerability of a system exists at the entry and exit points within the system. Figure shows an e-Commerce system with several points that the attacker can target: •

Shopper

•

Shopper' computer

•

Network connection between shopper and Web site's server

•

Web site's server

•

Software vendor

Tricking the shopper: Some of the easiest and most profitable attacks are based on tricking the shopper, also known as social engineering techniques. These attacks involve surveillance of the shopper's behavior, gathering information to use against the shopper. For example, a mother's maiden name is a common challenge question used by numerous sites. If one of these sites is tricked into giving away a password once the challenge question is provided, then not only has this site been compromised, but it is also likely that the shopper used the same logon ID and password on other sites. Snooping the shopper's computer: Millions of computers are added to the Internet every month. Most users' knowledge of security vulnerabilities of their systems is vague at best. A popular technique for gaining entry into the shopper's system is to use a tool, such as SATAN, to perform port scans on a computer that

detect entry points into the machine. Based on the opened ports found, the attacker can use various techniques to gain entry into the user's system. Upon entry, they scan your file system for personal information, such as passwords. A user that purchases firewall software to protect his computer may find there are conflicts with other software on his system. To resolve the conflict, the user disables enough capabilities to render the firewall software useless. Sniffing the network: In this scheme, the attacker monitors the data between the shopper's computer and the server. There are points in the network where this attack is more practical than others. If the attacker sits in the middle of the network, then within the scope of the Internet, this attack becomes impractical. A request from the client to the server computer is broken up into small pieces known as packets as it leaves the client's computer and is reconstructed at the server. The packets of request are sent through different routes. The attacker cannot access all the packets of a request and cannot decipher what message was sent. Guessing passwords: Another common attack is to guess a user's password. This style of attack is manual or automated. Manual attacks are laborious, and only successful if the attacker knows something about the shopper. For example, if the shopper uses their child's name as the password. Using server root exploits: Root exploits refer to techniques that gain super user access to the server. This is the most coveted type of exploit because the possibilities are limitless. When you attack a shopper or his computer, you can only affect one individual. With a root exploit, you gain control of the merchants and all the shoppers' information on the site. There are two main types of root exploits: buffer overflow attacks and executing scripts against a server. DEFENSES Despite the existence of hackers and crackers, e-Commerce remains a safe and secure activity. The resources available to large companies involved in eCommerce are enormous. These companies will pursue every legal route to protect their customers. Figure 6 shows a high-level illustration of defenses available against attacks.

Education: Your system is only as secure as the people who use it. If a shopper chooses a weak password, or does not keep their password confidential, then an attacker can pose as that user. Users need to use good judgment when giving out information, and be educated about possible phishing schemes and other social engineering attacks. Personal firewalls: When connecting your computer to a network, it becomes vulnerable to attack. A personal firewall helps protect your computer by limiting the types of traffic initiated by and directed to your computer. The intruder can also scan the hard drive to detect any stored passwords. Secure Socket Layer (SSL): Secure Socket Layer (SSL) is a protocol that encrypts data between the shopper's computer and the site's server. When an SSL-protected page is requested, the browser identifies the server as a trusted entity and initiates a handshake to pass encryption key information back and forth. Now, on subsequent requests to the server, the information flowing back and forth is encrypted so that a hacker sniffing the network cannot read the contents. The SSL certificate is issued to the server by a certificate authority authorized by the government. When a request is made from the shopper's browser to the site's server using https://..., the shopper's browser checks if this site has a certificate it can recognize. If the site is not recognized by trusted certificate authority, then the browser issues a warning as shown in Figure

Figure

For example in mozilla: Figure Secure icon in Mozilla Firefox

Server firewalls: A firewall is like the moat surrounding a castle. It ensures that requests can only enter the system from specified ports, and in some cases, ensures that all accesses are only from certain physical machines. A common technique is to setup a demilitarized zone (DMZ) using two firewalls. The outer firewall has ports open that allow ingoing and outgoing HTTP requests. This allows the client browser to communicate with the server. A second firewall sits behind the e-Commerce servers. This firewall is heavily fortified, and only requests from trusted servers on specific ports are allowed through. Both firewalls use intrusion detection software to detect any unauthorized access attempts. Figure shows the firewalls and honey pots.

Password policies: Ensure that password policies are enforced for shoppers and internal users. You may choose to have different policies provided by federal information standard, shoppers versus your internal users. For example, you may choose to lockout an administrator after 3 failed login attempts instead of 6. These password policies protect against attacks that attempt to guess the user's password. They ensure that passwords are sufficiently strong enough so that they cannot be easily guessed. Site development best practices There are many established policies and standards for avoiding security issues. However, they are not required by law. Some of the basic rules include: •

Never store a user's password in plain text or encrypted text on the system. Instead, use a one-way hashing algorithm to prevent password extraction.

•

Employ external security consultants (ethical hackers) to analyze your system.

•

Standards, such as the Federal Information Processing Standard (FIPS), describe guidelines for implementing features. For example, FIPS makes recommendations on password policies, etc.

Security best practices remain largely an art rather than a science, but there are some good guidelines and standards that all developers of e-Commerce software should follow. Using cookies

One of the issues faced by Web site designers is maintaining a secure session with a client over subsequent requests. Because HTTP is stateless, unless some kind of session token is passed back and forth on every request, the server has no way to link together requests made by the same person. Cookies are a popular mechanism for this. An identifier for the user or session is stored in a cookie and read on every request. You can use cookies to store user preference information, such as language and currency. The primary use of cookies is to store authentication and session information, your information, and your preferences. A secondary and controversial usage of cookies is to track the activities of users. Using an online security checklist Use this security checklist to protect yourself as a shopper: some of the checks will be like: •

Whenever you logon, register, or enter private information, such as credit card data, ensure your browser is communicating with the server using SSL.

•

Use a password of at least 6 characters, and ensure that it contains some numeric and special characters (for example, c0113g3).

•

Avoid reusing the same user ID and password at multiple Web sites.

•

If you are authenticated (logged on) to a site, always logoff after you finish.

•

Use a credit card for online purchases. Most credit card companies will help you with non-existent or damaged products.

Using threat models to prevent exploits: When architecting and developing a system, it is important to use threat models to identify all possible security threats on the server. Think of the server like your house. It has doors and windows to allow for entry and exit. These are the points that a burglar will attack. A threat model seeks to identify these points in the server and to develop possible attacks. Threat models are particularly important when relying on a third party vendor for all or part of the site's infrastructure. This ensures that the suite of threat models is complete and up-to-date.

Conclusion This article outlined the key players and security attacks and defenses in an eCommerce system. Current technology allows for secure site design. It is up to the development team to be both proactive and reactive in handling security threats, and up to the shopper to be vigilant when shopping online. Resources •

Learn about social factors in computer security. Schneier, Bruce. Secrets and Lies: Digital Security In A Networked World, John Wiley and Sons, Inc., 2000.

•

A good introduction to computer security. Pfleeger, Charles P., Security in Computing, Second Edition, Prentice-Hall, Inc., 1996.

•

Low level tips for writing secure code. Howard, Michael and LeBland, David, Writing Secure Code, Second Edition, Microsoft Press, 2003.

•

An example of a denial of service attack. Yahoo on Trail of Site Hackers, Reuters News Service, February 8, 2000.

PAPER PRESENTATION ON

DATA WAREHOUSING & MINING FOR

RIP PL E2K7 IX NATIONAL LEVEL STUDENT TECHNICAL SYMPOSIUM FOR PAPER PRESENTATION

HELD ON 29th December 2007 Presented by:1. A.MADHAVI LATHA III – CSE B Phone 9959276798 E-mail: [email protected] 2. A. PRAGNYA II – CSE A Phone 9966829702 E-mail: [email protected] FROM

KURNOOL

ABSTRACT Data warehousing is the process where organizations extract value from their informational assets though the use of special stores called data warehouses. In general data warehouse is defined to be subject-oriented, integrated, time-variant, and non-volatile.

Using both internal and external

systems sources of data, a data warehouse is created. Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data Warehouses are increasingly used by enterprises to increase efficiency and competitiveness. Using Scorecarding, Data Mining and on-line analytical processing (OLAP) analysis, business value can be extracted from Data Warehouses. Generating positive return-on-investments (ROI) from Data Warehouses requires a blend of business intuitiveness and technical skills. This paper presents these strategies and technologies that will enhance the ROI of Data Warehousing. INTRODUCTION Database management

Systems (DBMS)

operational transaction processing systems.

is mostly associated with

While DBMS help in automating

day-to-day operations of organizations, data is often locked up within each transaction processing system and could not be used effectively for organization wide information retrieval and decision support functions.

The need for

enterprise wide integrated information retrieval for decision making is the basis for data warehousing. Data warehousing primarily deals with gathering data from multiple transaction

processing systems and external sources, ensuring data warehousing quality, organizing the data warehousing for information processing, and providing information retrieval and analysis through on-line analytical processing (OLAP), reporting, web-based and data mining tools. Data Mining is the discovery of useful patterns in data. Data mining are used for prediction analysis and classification - e.g. what is the likelihood that a customer will migrate to a competitor. Data mining, the extraction of hidden predictive information from large databases, it helps the companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions.

The

automated, prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. Data Mining is the automated discovery of patterns in data. Data Mining can be used for predictive analysis in marketing to comparison of gene sequences in bio technology. Often Data Mining is used together with OLAP for data analysis. DATA WAREHOUSING Data warehouse is a combination of data from all types of sources and have the following characteristics: subject oriented, integrated, time-variant, and non-volatile. Data warehouses are specifically designed to maximize performance on queries run against them for analysis. Data warehousing

is open to an almost

limitless range of definitions. Simply put, Data Warehouses store an aggregation of a company's data. Data Warehouses are an important asset for organizations to maintain efficiency, profitability and competitive advantages. Organizations collect data through

many

sources

-

Online,

Call

Center,

Sales

Leads,

Inventory

Management. The data collected have degrees of value and business relevance.

77

As data is collected, it is passed through a 'conveyor belt', call the Data Life Cycle Management. An organization's data life cycle management's policy will dictate the data warehousing design and methodology.

Figure1. Overview of Data Warehousing Infrastructure The goal of Data Warehousing is to generate front-end analytics that will support business executives and operational managers. Pre-Data Warehouse The pre-Data Warehouse zone provides the data for data warehousing. Data Warehouse designers determine which data contains business value for insertion. OLTP databases are where operational data are stored. OLTP databases can reside in transactional software applications such as Enterprise Resource Management (ERP), Supply Chain, Point of Sale, and Customer Serving Software. OLTPs are design for transaction speed and accuracy. Metadata ensures the sanctity and accuracy of data entering into the data lifecycle process. Meta-data ensures that data has the right format and relevancy. Organizations can take preventive action in reducing cost for the ETL

78

stage by having a sound Metadata policy. The commonly used terminology to describe Metadata is "data about data". Data Cleansing Before data enters the data warehouse, the extraction, transformation and cleaning (ETL) process ensures that the data passes the data quality threshold. ETLs are also responsible for running scheduled tasks that extract data from OLTPs. Data Repositories The Data Warehouse repository is the database that stores active data of business value for an organization. The Data Warehouse modeling design is optimized for data analysis.

There are variants of Data Warehouses - Data

Marts and ODS. Data Marts are not physically any different from Data Warehouses. Data Marts can be though of as smaller Data Warehouses built on a departmental rather than on a company-wide level.

Data Warehouses collects

data and is the repository for historical data. Hence it is not always efficient for providing up-to-date analysis. This is where ODS, Operational Data Stores, come in. ODS are used to hold recent data before migration to the Data Warehouse. ODS are used to hold data that have a deeper history that OLTPs. Keep large amounts of data in OLTPs can tie down computer resources and slow down processing - imagine waiting at the ATM for 10 minutes between the prompts for inputs. . Front-End Analysis The last and most critical potion of the Data Warehouse overview are the frontend applications that business users will use to interact with data stored in the repositories. DATA LIFE CYCLE MANAGEMENT

79

Data becomes active as soon as it is of interest to an organization. Data life cycle begins with a business need for

acquiring data. Active data are referenced

on a

regular basis during day-to-day business operations. Over time, this data loses its importance and is accessed less often, gradually losing its business value, and ending with its archival or disposal.

Figure1. Data Life Cycle in Enterprises Active Data Active data is of business use to an organization. The ease of access for business users to active data is an absolute necessity in order to run an efficient business. All data moves through life-cycle stages is key to improving data management. By understanding how data is used and how long it must be retained, companies can develop a strategy to map usage patterns to the optimal storage media, thereby minimizing the total cost of storing data over its life cycle, when data is stored in a relational database, although the challenge of managing and storing relational data is compounded by complexities inherent in data relationships. Inactive Data Data are put out to pasture once they are no longer active. I.e. there are no longer needed for critical business tasks or analysis. Prior to the mid-nineties, most enterprises achieved data

in Microfilms and tape back-ups.

There are now technologies for data archival such as (SAN),

Storage Area Networks

Network Attached Storage (NAS ) and

80

Hierarchical Storage

Management . These storage systems can maintain referential integrity and business context. What is OLAP? OLAP allows business users to slice and dice data at will. Normally data in an organization is distributed in multiple data sources and are incompatible with each other. A retail example: Point-of-sales data and sales made via call-center or

the

Web are

stored

in different location

and

formats.

It would a time consuming process for an executive to obtain OLAP reports. Figure4. Steps in the OLAP Creation Process Part of the OLAP implementation process involves extracting data from the various data repositories and making them compatible. Making data compatible involves ensuring that the meaning of the data in one repository matches all other repositories. It is not always necessary to create a data warehouse for OLAP analysis. Data stored by operational systems, such as point-of-sales, are in types of databases called OLTPs. OLTP,

Online Transaction Process , databases do

not have any difference from a structural perspective from any other databases. The main difference and only, difference is the way in which data is stored. Examples of OLTPs can include ERP, CRM, SCM, Point-of-Sale applications, Call Center. OLTPs are designed for optimal transaction speed. When a consumer makes a purchase online, they expect the transactions to occur instantaneously. Next cubes for OLAP database are built and at last Reports are produced.

81

DATA MINING Data Mining is the automated discovery of patterns in data. Data Mining can be used for predictive analysis in marketing to comparison of gene sequences in bio technology. Often Data Mining is used together with OLAP for data analysis. Integrated Data Mining and OLAP for MySQL DAT-A is a data mining and OLAP platform for MySQL. The goals of DAT-A are to design a high-end analytical product from the needs of the end-user and then follow through on the technology. Data mining software are noted for their lack of ease of usability. This together with the abstract nature of analytics has meant that there has been a relatively low pick-up of data mining in the commercial world. Data mining has a useful role to play but very often the total cost of ownership far out weighs any business benefits. Biotechnological and financial firms find data mining an absolute part of their competitive advantage. However these industries find the cost of running data warehouses and perform analytics can be an expensive burden. Data collected by businesses are increasing at a large rate. Most data have business relevancy and cannot be simply shunted to archive storage should the cost of storage increase. This is especially valid for analytics where trends need to

be

observed

over

an

extended period for greater accuracy. The

data

mining

center

solution

and

data

below

was

designed for a retail client who had global operations. Retail is a high cost low margin (HCLM) and an extremely competitive industry. The cost for data

82

storage in an active medium was proving prohibitive for the client. For competitive reasons it was not possible to simply ignore the data and par down cost.

A

distributed

data

center

was

designed

replacing

the

mainframe

environment that existed previously and presented management with an alternative to expensive server environment, using a cluster of over 200 Linux boxes powered by MySQL databases. Figure1. Data Cluster using Linux Boxes Using commodity Linux boxes offered a tremendous cost savings over servers. As the amount of data stored exceeded the terabyte range it was prudent to index the data and store in a distributed manner over the data cluster. MySQL was not quite an obvious choice as it may have seemed. While extremely fast and reliable, MySQL does not have many sophisticated features that are needed for data warehousing and data mining. This hurdle was overcome by using

a

database

transaction

engine

from

InnoDB .

Remote

database

management systems were built for the MySQL/Linux cluster that allows data administrators to visualize the "data spread" over the center - this is similar to a table view found in most of the popular RDBMS databases. The data spread diagram gave the data administrators, an ability to manipulate and transfer data from afar without the need to logon to the individual box. The data spread application also allowed the user to build data cubes for OLAP analysis.

There are two

methods by which users can perform data mining - the first using a stovepipe approach that packages the business needs tightly together with the data mining algorithms. This first method allowed business users to directly perform data mining and the user is given limited latitude in choosing the methodologies. The second method gave freedom to explore data and choose a number of algorithms. The types of user envisioned for the second method are more seasoned data miners.

83

Intelligent Data Mining Open source application for data mining on MySQL Data mining has had technical constrains placed by limitations of software design and architecture. Most of the algorithms used in data mining are mature for over 20yr. The next challenges in data mining are not algorithmic but s/w design methodologies. Commonly used data mining algorithms are freely available and processes that optimize data mining computing speed are well documented. Data access standards such as OLE-DB, XML for Analysis and JSR will minimize the challenges for data access. Building a user friendly software interfaces for the end-user are the next steps in the evolution of data mining. A comparable analogy can be made with the increasing ease of use of OLAP client tools. The J2EE and .NET software platforms offer a large spectrum of built-in APIs that enable smarter software applications. Text Mining Text mining has been on the radar screen of corporate users since the mid-eighties. Technical limitations and the overall complexity of utilizing data mining has been a hurdle to text mining that has been surmounted by very few organizations. Text mining is coming out into the open. Some of the reasons are: •

Storage cost reduction - data are stored in an electronic medium even after being declared non-active.

•

Data volume increase - the exponential growth of data with the lowering of data transmission cost and increasing usage of the Internet.

•

Fraud detection and analysis - there are compelling reasons for organizations to redress fraud.

•

Competitive advantage - It is used to better understand the realms of data in an organization.

84

Text data is so called unstructured data. Unstructured data implies that the data are freely stored in flat files (e.g. Microsoft Word) and are not classified. Structured data are found in well-designed data warehouses. The meaning of the data is well-known, usually through meta-data description, and the analysis can be performed directly on the data.

Unstructured data has to jump an additional hoop before it can be

meaningfully analyzed - information will need to be extracted from the raw text. Text Mining for Fraud Detection Creating cost effective data mining solutions for fraud analysis For fraud detection, the client currently had a distinct data repository where model scoring was performed. Based on the model score, reports would be queried against the data warehouse to produce the claims that were suspect. This process was inefficient for a number of reasons: • Fraud detection analysis had to be conducted by a specialist who passed the

scores onto the fraud detection team. The team performed the investigation and evaluated the merits of the claims. This was a disjointed process whereby the fraud detection data mining scores were not being improved based on investigation results. • Fraud detection was not receptive to sudden changes in claim patterns. For

natural disaster events, such as hurricanes, there would be a spike in similar claims. The data mining score would not be able to adapt to such scenarios. • Data

mining was confined to actuarial specialists and not day-to-day

managers. Developing a Customized Text Mining Solution The customized solution was developed in three modules. A scripting engine was designed and developed for the data extraction layer. The data extraction layer was designed to pull reports, either manually or as a scheduled task, from the data warehouse repositories. The reports created by the claims examiners are stored in Microsoft Word and follow the guidelines set by the

85

metadata repository. The scripting language used by the data extraction module is Perl, which makes the extraction module highly accessible for making changes by end-users. Figure1. Text Mining Modules The text mining module contains the data mining scores based on historically analysis of likelihood of fraud. The algorithms were custom developed based on text entered in the claims examiner's reports and details based on the claim. The data mining model can give the client a competitive advantage and the technical details are kept as a closely guarded corporate secret. Reports are generated on a web-based application layer. The data produced for the reports are also fed into the SAP for Insurance ERP application which is used by the client and commonly found in most of the larger insurance companies. Figure 2 Process Chart for Conducting Text Mining Many text mining applications give users openended freedom to explore text for meaning. Text mining can be used as a deeper more penetrative

method

which

goes

beyond

escalations of possible search interests and to sense the mood of the written text; i.e. are the articles generally positive on a certain subject? While such open-ended undirected data mining may be suitable in some cases of text mining, the cost associated can be very high and the results will have a lower confidence of accuracy.

86

Future of Data Mining Data mining is the analysis of large data sets to discover patterns of interests. Data mining has come a long way from the early academic beginnings in the late seventies. Many of the early data mining software packages were based on one algorithm.

Until the mid-nineties data

mining required considerable specialized knowledge and was mainly restricted to statisticians.

Customer

Relationship

Management (CRM) software played a great part in popularizing data mining among corporate users. Data mining in CRMs are often hidden from the end users. The algorithms are packaged behind business functionality such as Churn analysis. Churn analysis is the process to predict which customers are the ones most likely to defect to a competitor. Data mining algorithms are now freely available. Database vendors have started to incorporate data mining modules. Developers can now access data mining via open standards such as OLE-DB for data mining on SQL Server 2000. Data mining functionality can now be added directly to the application source code. CONCLUSION Data warehousing and mining, architecture is used to tie together a wide range of information technology, this architecture also help to integrate and tie together the business purpose and enterprise architecture of data warehousing solutions. OLAP is best used for power IT users and finance/accounting users who like the spreadsheet based presentation.

87

The value of relationship mining can be a useful tool not only in sales and marketing but also for law enforcement and science research. However there is a threshold barrier under which relationship mining would not be cost effective. Text mining has reduced complexity of utilizing data mining. The security agencies have a government mandate to intercept data traffic and evaluate for items of interest. This also involves intercepting international fax transmission electronically and mining for patterns of interest. In the future of the Data mining, we hide the complexity of data mining from the end-users before it will take the true center stage in an organization. Business use cases can be designed, with tight constrains, around data mining algorithms References: 1. http://www.dwreview.com “ Data warehousing and mining”

2. Meta Group Application Development Strategies: “Data Mining for Data Warehouses”

VISUAL KEYBOARD (AN APPLICATION OF DIGITAL IMAGE SCANNING) B.Anusha.

88

T.Hima bindu. V.R.SIDDHARTHA ENGINEERING COLEGE. Vijaywada. Ph no:9490907741.

ABSTRACT Information and communication technologies can have a key role in helping people with educational needs, considering both physical and cognitive disabilities. Replacing a keyboard or mouse, with eye-scanning cameras mounted on computers have become necessary tools for people without limbs or those affected with paralysis. The camera scans the image of the character, allowing users to ‘type’ on a monitor as they look at the visual keyboard. The paper describes an input device, based on eye scanning techniques that allow people with severe motor disabilities to use gaze for selecting specific areas on the computer screen. It includes a brief description of eye, about the visual key system where it gives overall idea on how does this process goeson, also deals with the system architecture which includes calibration, image acquisition, segmentation, recognition, and knowledge base. The paper mainly includes three algorithms, one for face position, for eye area identification, and for pupil identification which are based on scanning the image to find the black pixel concentration.Inorder to implement this we use software called dasher, which is highly appropriate for computer users who are unable to use a two handed keyboard. One-handed users and users with no hands love dasher. The only ability that is required is sight. Dashers along with eye tracking devices are used. This model is a novel idea and the first of its kind in the making, which reflects the outstanding thinking of a human that he left no stone unturned.

1. INTRODUCTION

89

‘Vis-Key’ aims at replacing the conventional hardware keyboard with a ‘Visual Keyboard’. It employs sophisticated scanning and pattern matching algorithms to achieve the objective. It exploits the eyes’ natural ability to navigate and spot familiar patterns. Eye typing research extends over twenty years; however, there is little research on the design issues. Recent research indicates that the type of feedback impacts typing speed, error rate, and the user’s need to switch her gaze between the visual keyboard and the monitor. 2. THE EYE

Fig 2.1 shows us the horizontal cross section of the human eye. The eye is nearly a sphere with an average diameter of approximately 20mm.Three membranes – The Cornea &Sclera cover, the Choroids layer and the Retina – encloses the eye. When the eye is properly focused, light from an object is imaged on the retina. Pattern vision is afforded by the distribution of discrete light receptors over the surface of the Retina. There are two classes of receptors – Cones and Rods. The cones, typically present in the central portion of the retina called fovea is highly sensitive to color. The number of cones in the human eye ranges from6-7 millions. These cones can resolve fine details because they are connected to its very own

90

nerve end. Cone vision is also known as Photopic or Bright-light vision. The rods are more in

number when compared to the cones (75-150 million). Several rods are

connected to a single nerve and hence reduce the amount of detail discernible by the receptors. Rods give a general overall picture of the view and not much inclined towards color recognition. Rod vision is also known as the Scotopic vision or Dimlight vision as illustrated in fig 2.1, the curvature of the anterior surface of the lens is greater than the radius of its posterior surface. The shape of the lens is controlled by the tension in the fiber of the ciliary body. To focus on distant objects , the controlling muscles cause the lens to be relatively flattened. Similarly to focus on nearer objects the muscles allow the lens to be thicker. The distance between the focal distance of the lens and the retina varies from 17 mm to 14 mm as the refractive power of the lens increases from its minimum to its maximum. 3. The Vis-Key System The main goal of our system is to provide users suffering from severe motor disabilities (and that therefore are not able to use neither the keyboard nor the mouse) with a system that allows them to use a personal computer.

Fig 3.1 System Hardware of the Vis-Key System The Vis-Key system (fig 3.1) comprises of a High Resolution camera that constantly scans the eye in order to capture the character image formed on the Eye. The camera gives a continuous streaming video as output. The idea is to capture individual frames at regular intervals (say ¼ of a second). These frames are then compared with the base frames stored in the repository. If the

91

probability of success in matching exceeds the threshold value, the corresponding character is displayed on the screen. The hardware requirements are simply a personal computer, Vis-Key Layout (chart) and a web cam connected to the USB port. The system design, which refers to the software level, relies on the construction, design and implementation of image processing algorithms applied to the captured images of the user. 4. System Architecture: 4.1. Calibration

92

The calibration procedure aims at initializing the system. The first algorithm, whose goal is to identify the face position, is applied only to the first image, and the result will be used for processing the successive images, in order to speed up the process. This choice is acceptable since the user is supposed only to make minor movements. If background is completely black (easy to obtain) the user’s face appears as a white spot, and the borders can be obtained in correspondence of a decrease in the number of black pixels. The Camera position is below the PC monitor; if it were above, in fact, when the user looks at the bottom of the screen the iris would be partially covered by the eyelid, making the identification of the pupil very difficult. The user should not be distant from the camera, so that the image does not contain much besides his/her face. The algorithms that respectively identify the face, the eye and the pupil, in fact, are based on scanning the image to find the black pixel concentration: the more complex the image is, the slowest the algorithm is too. Besides, the image resolution will be lower. The suggested distance is about 30 cm. The user’s face should also be very well illuminated, and therefore two lamps were posed on each side of the computer screen. In fact, since the identification algorithms work on the black and white images, shadows should not be present on the User’s face. 4.2. Image Acquisition: The Camera image acquisition is implemented via the Functions of the AviCap window class that is part of the Video for Windows (VFW) functions. The entire image of the problem domain would be scanned every 1/30 of second .The output of the camera is fed to an Analog to Digital converter (digitizer) and digitizes it. Here we can extract individual frames from the motion picture for further analysis and processing. 4.3. Filtering of the eye component: The chosen algorithms work on a binary (black and white) image, and are based on extracting the concentration of black Pixels. Three algorithms are applied to the first acquired image, while from the second image on only the third one is applied

93

Fig Algorithm

4.3.1 1

–

Face Positioning image, from

the

while First

algorithm, whose goal is to identify the face position, is applied only to the first image, and the result will be used for processing the successive images, in order to speed up the process. This choice is acceptable since the user is supposed only to make minor movements. The Face algorithm converts the image in black and white, and zooms it to obtain an image that contains only the user’s face. This is done by scanning the original image and identifying the top, bottom, left and right borders of the face. (Fig 4.3.1).Starting from the resulting image, the Second algorithm extracts the information about the eye position (both left and right) pixels is the one that contains the eyes. The algorithm uses this information to determine the top and bottom borders of the eyes area (Fig.4.3.2), so that it is extracted from the image. The new image is then analyzed to identify the eye: the algorithm finds the right and left borders, and generates a new image containing the left and right eyes independently

94

The procedure described up until now is applied only to the first image of the sequence, and the data related to the right eye position are stored in a buffer and used also for the following images. This is done to speed up the process, and is acceptable if the user does only minor head movements. The Third algorithm extracts the position of the center of the pupil from the right eye image. The Iris identification procedure uses the same approach of the previous algorithm .First of all, the left and right borders of the iris are extracted. Finding the top and bottom ones would be less precise due to the eyelid presence, so a square area is built, that slides over the image. The chosen area, which represents the iris, is the one that has the higher concentration of black pixels. The center of this image represents also the center of the pupil. The result of this phase is the coordinates of the center of the pupil for each of the image in the sequence.

4.4. Preprocessing: The key

function

preprocessing

of is

to

95

improve the image in ways to improve the chances for success with other processes. Here preprocessing deals with 4 important techniques: •

To enhance the contrast of the image.

•

To eliminate/minimize the effect of noise on the image.

•

To

isolate

regions

whose

texture

indicates

likelihood

to

alphanumeric

information? •

To provide equalization for the image.

4.5. Segmentation: Segmentation broadly defines the partitioning of an input image into its constituent parts or objects. In general, autonomous segmentation is one of the most difficult tasks in Digital Image Processing. A rugged segmentation procedure brings the process a long way towards Successful solution of the image problem. In terms of character recognition, the key role of segmentation is to extract individual characters from the problem domain. The output of the segmentation stage is raw pixel data, constituting either the boundary of a region or all points n the region itself. In either case converting the data into suitable form for computer processing is necessary. The first decision is to decide whether the data should be represented as a boundary or as a complete region. Boundary representation is appropriate when the focus is on external shape characteristics like corners and inflections. Regional representation is appropriate when the focus is on internal shape characteristics such as texture and skeletal shape Description also called feature selection deals with extracting features that result in some quantitative information of interest or features that are basic for differentiating one class of objects from another. 4.6. Recognition and Interpretation: Recognition is the process that assigns a label to an object based on the information provided by its descriptors. This process allows us to cognitively recognize characters based on knowledge base meaning to an ensemble of recognized objects. Interpretation attempts to assign meaning to a set of labeled entities. For example, to identify character say 'C', we need to associate descriptors for that character with label 'C'.

96

4.7. Knowledge Base: Knowledge about a particular problem domain can be coded into an image processing system in the form of a knowledge database. The knowledge may be as simple as detailing regions of an image where the information of interest is known thus limiting our search in seeking that information. Or it can be quite complex such as an image entries are of high resolution. The key distinction of this knowledgebase is that it, In addition to guiding the operation of various components, facilitates feedback operations of various modules of the system. This depiction on FIG 4.1 indicated that communication between processing modules is based on prior knowledge of what a result should be. 5. Design Constraints: Though this model is thought provoking, we need to address the design constraints as well. 

R & D constraints severely hamper our cause for a full-fledged working model of the Vis-Key system.

 The need for a very high resolution camera calls for a high initial investment. 

The accuracy and the processing capabilities of the algorithm are very much liable to quality of the input.

6. Alternatives/Related References: The approaches till date have only been centered on the eye tracking theory. It lays more emphasis on the use of eye as a cursor and not as a data input device. An eye tracking device lets users select the letters from a screen. Dasher, the prototype program taps in to the natural gaze of the eye and makes predictable words and phrases simpler to write.

97

Dasher is software which is highly appropriate for computer users. It calculates the probability of one letter coming after another. It then presents the letters required as if contained on infinitely expanding bookshelves. Researchers say people will be able to write up to 25 words per minute with Dasher compared to on-screen keyboards, which they say average about 15 words per minute. Eye-tracking devices are still problematic. "They need re-calibrating each time you look away from the computer," says Willis. He controls Dasher using a trackball. 7. CONCLUSION: It opens a new dimension to how we perceive the world and should prove to be a critical technological break through considering the fact that there has not been sufficient research in this field of eye scanning. If implemented, it will be one of the AWE-INSPIRING technologies to hit the market.

Bibliography: ü http://www.cs.uta.fi/~curly/publications/ECEM12-Majaranta.html ü www.inference.phy.cam.ac.uk/djw30/dasher/eye.html

98

ü http://www.inference.phy.cam.ac.uk/dasher/ ü http://www.cs.uta.fi/hci/gaze/ eyetyping.php ü http://www.acm.org/sigcaph ü Ward, D. J. & MacKay, D. J. C. “Fast hands-free writing by gaze direction.” Nature, 418, 838, (2002). ü Daisheng Luo “Pattern Recognition and Image Processing” Horwood series in engineering sciences

DEPARTMENT OF COMPUTER SCIENCE ENGINEERING

DVR & Dr. HS MIC College of Technology

Kanchikacherala DIGITAL IMAGE PROCESSING

PAPER PREPARED BY: Srikanth M

Pradeep S

III yr CSE

III yr CSE

E-MAIL: [email protected]

99

[email protected] Abstract Interest in digital image processing methods stems from two principal application areas: improvement pictorial information for human interpretation; and processing of image data for storage, transmission, and representation for autonomous machine perception. Digital image processing refers to processing digital images by means of a digital computer. Note that digital image is composed of finite number of elements, each of which has a particular location and value. There will be disturbances in every aspect digital image processing has no exception. Digital image processing also suffers from some sort of disturbances from external sources and others. This is going to be discussed in this aspect. As we know that the images could be in the form of analog signals there is a need to convert these signals to digital form which can be done by plotting the image using different transfer functions which are explained here under. A transfer function maps the pixel values from the CCD (Charge coupled device) to the available brightness values in the imaging software all the images so far have been plotted using linear transfer functions Filter masks and other manipulations have also discussed in this aspect in order to make the image filter and get a clear cut form of the image. Introduction What is digital image processing? A digital image is picture which is divided into a grid of “pixels” (picture elements). Each pixel is defined by three numbers(x, y, z), and displayed on a computer screen.

100

The first two numbers give the x and y coordinates of the pixel, and the third gives its intensity, relative to all the other pixels in the image.

The

intensity

is

a

relative measure of the number of photons collected at that photosite on the CCD, relative to all the others, for that exposure. The clarity of a digital image depends on the number of “bits” the computer uses to represent each pixel. The most common type of representation in popular usage today is the “8-bit image”, in which the computer uses 8 bits, or 1 byte, to represent each pixel. This yields 28 or 256 brightness levels available within a given image.

These

brightness levels can be used to create a black-and-white image with shades of gray between black (0) and white (255), or assigned to relative weights of red, green, and blue values to create a color image. The range of intensity values in an image also depends on the way in which a particular CCD handles its ANALOG TO DIGITAL (A/D) conversion. 12-bit A/D conversion means that each image is capable of 212(4096) intensity values. If the image processing program only handles 28(256) brightness levels, these must be divided among the total range of intensity values in a given image. Below histogram shows the number of pixels in a 12-bit image that have the same intensity, from 0 to 4095. Suppose u have software that only handles 8-bit information you assign black and white limits, so that all pixels with values to the left of the lower limit are set to 0, while all those to the right of the upper limit are set to 255. This allows u to look at details within a given intensity range.

101

So, a digital image is a 2-dimensional array of numbers, where each number represents the amount of light collected at one photosite, relative to all the other photosites on the CCD chip. It might look something like…. •

98 107 145 126 67 93 154 223 155 180 232 250 242 207 201

•

72 159 159 131 76 99 245 211 165 219 222 181 161 144 131

•

157 138 97 106 55 131 245 202 167 217 173 127 126 136 129

•

156 110 114 91 70 128 321 296 208 193 191 145 422 135 138

By this we can guess the brightest pixel in the “image”…

Correcting the raw image Every intensity value contains both signal and noise. Your job is to extract the signal and eliminate the noise! But before that the sources of noise should be known. They can be a)

The Dark Current:

Since electrons in motion through a metal or semiconductor create a current, these thermally agitated electrons are called the Dark Current. …so, to eliminate thermal electrons, the CCD must be COOLED as much as possible.

The cooler one can make one’s CCD, the less dark current one will

generate. In fact, the dark current decreases roughly by a factor of 2 for every 7 0c

102

drop in temperature of the chip. At – 1000c the dark current is negligible. When you process an image correctly, you must account for this dark current, and subtract it out from the image. This is done by taking a “closed shutter” image of a dark background, and then subtracting this dark image from the “raw” image you are observing. The exposure time of the dark image should match that of the image of the object or starfield you are viewing. In fact, the one who regularly take CCD image keep files of dark current exposures that match typical exposure times of images they are likely to take, such as: 10,20,45,60or 300 seconds, which are updated regularly, if not nightly. b)

The Bias Correction

CCD cameras typically add a bias value to each image they record. If you know that the same specific bias value has been added to each pixel, you can correct for this by subtracting a constant from your sky image. c)

Pixel – to – pixel Sensitivity variation Another source of noise is the inherent variation in the response of each pixel to

incident radiation. Ideally, if your CCD is functioning properly, there should be no variation in pixel value when you measure a uniformly–illuminated background. However, nothing I perfect, and there usually is some slight variation in the sensitivity of each photosite, even if the incident radiation is totally uniform. This can be accounted for by taking a picture of a uniformly bright field, and dividing the ray image by this “flat” field – a process called flat fielding. The length of time to expose the flat image should be enough to saturate the pixels to the 50% or 75% level. One must take 4 pictures before beginning to process the image. One needs 4 images to create a “noiseless” image of the sky. 1) The original; 2) A dark exposure of the same integration time as your original; 3) A flat exposure;

103

4) And another dark exposure, of the same integration time as your flat exposure! Final image =

raw image - dark (Flat - dark

raw

)

flat

(Don’t forget to subtract your dias correction form each image) So… the correct raw image taken with any CCD one must •

Subtract the bias correction form each image;

•

Subtract the dark current image from the raw image;

•

Subtract the dark current image form the flat field image;

•

Divide the dark – subtracted raw image by the dark- subtracted flat image. 3 ways of displaying your image to Enhance Certain Features

Once you have dark – subtracted and flat – fielded your image, there are many techniques you can use to enhance your signal, once you have eliminated the noise. These manipulations fall into two basic categories: 1)CHANGING THE WAY IN WHICH THE INFORMATION IS PLOTTED ON YOUR SCREEN These methods are basically mapping routines, and include: •

Limiting the visualization thresholds within the histogram

•

Plotting the image using different transfer functions

•

Histogram equalization

2)MATHEMATICAL METHODS OF MASSAGING YOUR DATA These methods employ various matrix multiplications, Fourier transformations, and convolutions, and we will address them in the next section. Limiting the visualization thresholds within the histogram We already saw that the histogram function shows you the distribution of brightness values in an image, and the number of pixels within the same brightness value. In the below histogram shown, most of the useful information is contained between the user-defined limits. The peak of intensities on the lower end could possibly be some faint feature, which could be enhanced in a variety of ways…

104

By changing the visualization limits in the histogram, the user can pre – define the black and white levels of the image, thus increasing the level of detail available in the mid – ranges of the intensities in a given image. Some examples of histogram limitation is used to examine different features

Plotting the image using different transfer functions A transfer function maps the pixel values from the CCD to the available brightness values in the imaging software all the images so far have been plotted using linear transfer functions …but you can also use non – linear scaling Human eyes see a wide range of intensities because our vision LONGARITHMICALLY scaled. When you plot digital images logarithmically, it allows you to see a broader range of intensities, and can give a more “natural” look… as if you could see the object with your naked eyes. …or, you could use a Power Law scaling Fractional powers enhance low intensity features, while powers greater than 1 enhance high intensity features.

105

HISTOGRAM EQUILIZATION It means of flattening your histogram by putting equal numbers of pixels in each “bin”, it serves to enhance mid – range features in an image with a wide range of intensity values. When you equalize your histogram, you distribute your 4096 intensity from your CCD equally among the intensity values available in your software. This can be particularly useful for bringing out features that close to the sky background, which would otherwise be lost.

After you have corrected your raw image so that you are confident that what you are seeing really come form incident photons and not electronic noise of your CCD. You may still have unwanted components in your image. It is time now to perform mathematical operations on your signal which

106

will enhance certain features, remove unwanted noise, smooth rough edges, or emphasize certain boundaries. ...and this brings us to our last topic for this module: Filters masks & other Mathematical Manipulations The rhyme and reason Basically, any signal contains information of varying frequencies and phases. In digital signal enhancement, we attempt to accentuate the components of that signal which carry the information we want, and reduce to insignificance those components which carry the noise. Audio equipment, such as your stereo or CD player, has filters which do this for one – dimensional, time – varying audio signal. In digital image analysis we extend these techniques to 2 – dimensional signals which are spatially varying. In any case, the basic idea is the same: Get the most out of your data For the least amount of hassle! Here’s how it Works: you create an “n X n” matrix of numbers, such as 3 X 3 or 5 X 5, and you move this across your image, like a little moving window, starting at the upper left corner (that’s 0,0,recall). You “matrix multiply” this with the pixel values in the image directly below it to get a new value for the center pixel. You move the window across your image, one pixel at a time, and repeat the operation, until you have changed the appearance of the entire image. Here’s an example of one kind of filter: 121 242

107

121 if you move this matrix across an image and matrix multiply along, you will end up replacing the center pixel in the window with the weighted average intensity of all the points located inside the window. HERE’S HOW TO DO IT: I11 I12 I13 I14 I15…

You plop this window down over a 3 X 3

I21 I22 I23 I24 I25 …

section

I31 I32 I33 I34 I35 …

multiplication on the center pixel, I22 in this

I41 I42 I43 I44 I45 …

example, and the new value for I22 which is

I51 I52 I53 I54 I55…

returned is

of

your

image,

do

a

matrix

1I11 + 2I12 + 1I13 + 2I21 + 4I22 + 2I23 + 1I31 + 2I32 + 1I33 I22’= ( 1+2+1+2+4+2+1+2+1 OR 16)

Imagine your image in 3 dimensions, where the intensity is plotted as height. Large scale features will appear as hills and valleys, while small bright objects like stars will appear as sharp spikes. Some features will have steep gradients, while others shallow. Some features may have jagged edges, while others are smooth. You can design little n X n windows to investigate and enhance these kinds of features of your image in the slides that follow, we will show examples of low Pass, high pass ,edge detection, gradient detection, sharpening, blurring, bias filtering your image. Low – pass filters enhance the larger scale feature in your image.

108

109

High pass filters enhance the short period features in your image, giving it a sharper look. Some examples of high pass filters: 0 -1 0

-1

0

20 -1 -1

0

0

-1

0

-1 10

-1

0

-1

0

-1

-1

-1

-1

-1

-1

-1 10

-1

-1 16

-1

-1

-1

-1

-1

-1

-1

Edge detection filters are used to locate the boundaries between regions of different intensities. The “bias filter” makes an image look like a bas relief with shadows. This can be useful for examining certain details You can also combine process – such as low pass, high pass, and image subtraction in a process called UNSHARP MASKING. Unsharp masking consists of a 3 – step process: 1.

Make a copy of the image where each pixel is the average of the

group of pixels surrounding it, so that the large features are not disturbed, but the small ones are blurred( this is the unsharp mask) 2.

The pixel values of the original image are multiplicated by a

constant (“A”), and then the pixel values of the unsharp mask are subtracted from this one or more times (“B”). In this way, the large features are not changed by much, but the small ones are enhanced. 3.

Finally a low – pass filter is applied to the result.

You can also create your own filter to smooth or otherwise operate on your image. Bibliography

1. Digital image processing by Rafael C. Gonzalez and Richard E. Woods 2. www.physics.ucsb.edu

UBIQUITOUS COMPUTING (PERVASIVE COMPUTING)

Presented By, B.DHEERAJ R.DEEPAK III/IV B.TECH III/IV B.TECH K.L.C.E K.L.C.E Email:[email protected] Email:[email protected] Abstract.

referred as

One is happy when

Ubiquitous

one’s desires are

computing through

fulfilled.

out the paper.

The highest ideal of

One of the goals of

Ubicomp is to make

ubiquitous

a computer so

computing is to

imbedded, so

enable devices to

fitting, so natural,

sense changes in

that we use it

their environment

without even

and to

thinking about it.

automatically adapt

Pervasive

and act based on

computing is

these changes

Page 111 of 216

based on user

operating systems,

needs and

user interfaces,

preferences. The

networks, wireless,

technology required

displays, and many

for ubiquitous

other areas. We call

computing comes in

our work

three parts: cheap,

“ubiquitous

low- power

computing”. This is

computers that

different from

include equally

PDA’s, dynabooks,

convenient

or information at

displays, a network

your fingertips. It is

that ties them all

invisible;

together, and

everywhere

software systems

computing that

implementing

does not live on a

ubiquitous

personal device of

applications.

any sort, but is in

Current trends

the woodwork

suggest that the

everywhere.

first requirement

Single-room

will easily be met.

networks based on

Our preliminary

infrared or newer

approach: Activate

electromagnetic

the world. Provide

technologies have

hundreds of

enough channel

wireless computing

capacity for

devices per person

ubiquitous

per office, of all

computers, but

scales. This has

they can only work

required network in

indoors.

Page 112 of 216

Cryptographic

Another term for this

techniques already

ubicomp is

exist to secure

PERVASIVE

messages from one

COMPUTING. This

ubiquitous

Ubicomp is roughly

computer to

the opposite of virtual

another and to

reality. Where virtual

safeguard private

reality puts people

information stored

inside a computer-

in networked

generated world, i.e.,

systems.

it forces the

We suggest using

computer to live out

cell phone device

here in the world with

available in the

people. Ubiquitous

market for Ubicomp

computing

also i.e., the

encompasses a wide

handheld device will

range of research

be used for both

topics, including

Ubicomp and also

distributed

as a cell phone.

computing, mobile computing, sensor networks, human-

How Ubiquitous

computer interaction,

Networking will

and artificial

work

intelligence.

Ubicomp integrates

By using a small

computation into the

radio transmitters

environment, rather

and a building full of

than having

special sensors, your

computers, which are

desktop can be

distinct objects.

anywhere you are. At

Page 113 of 216

the press of a button,

and receiver chains.

the computer closest to you in any room becomes your computer for long as you need it. In the Zone

Fig. 1. The ‘Bat’

In order for a

Users within the

computer program to

system will wear a

track its user a

bat, a small device

system should be

that transmits a 48-

developed that could

bit code to the

locate both people

receivers in the

and devices i.e.,

ceiling. Bats also

ultrasonic location

have an embedded

system. This location

transmitter, which

tracking system has

allows it to

three parts:

communicate with

Bats

:-

using a bi-directional

Small ultrasonic transmitters, worn by users. Receivers

the central controller

:-

433-MHz radio link. Bats are about the size of a paper. These small devices are

Ultrasonic signal

powered by a single

detectors embedded

3.6-volt lithium

in ceiling.

thionyl chloride

Central Controller

battery, which has a

:-

lifetime of six months. The devices

Co-ordinates the bats

also contain two

Page 114 of 216

buttons, two light-

sound at which the

emitting diodes and a

ultrasonic pulse

piezoelectric speaker,

reached three other

allowing them to be

sensors.

used as ubiquitous

By finding the

input and output

position of two or

devices, and a

more bats, the

voltage monitor to

system can

check the battery

determine the

status.

orientation of a bat.

A bat will transmit an

The central controller

ultrasonic signal,

can also determine

which will be

which way a person is

detected by receivers

facing by analyzing

located in the ceiling

the pattern of

approximately 4 feet

receivers that

apart in a square

detected the

grid. If a bat needs to

ultrasonic signal and

be located, the

the strength of the

central controller

signal.

sends the bats ID

The central controller

over a radio link to

crates a zone around

the bat. The bat will

every person and

detect its ID and

object within the

send out an

location system. The

ultrasonic pulse. The

computer uses a

central controller

spatial monitor to

measures the time it

detect if a user’s zone

looks for that pulse to

overlaps with the

reach the receiver.

zone of a device.

Since the speed of

Computer desktops

Page 115 of 216

can be created that actually follow their owners anywhere with in the system just by approaching any computer display in the building, the bat can enable the virtual network computing desktop to appear on that display. Ubi-Finger Here, in contrast, Ubi-Finger is the gesture-i/p device, which is simple, compact and optimized for mobile use. Using our systems, a user can detect a target device by pointing with his/her index finger, and then control it flexibly by performing natural gestures of fingers (Fig. 2).

By pointing a light

and making a

Page 116 of 216

gesture like “push

will turn on!

a switch”.The light Fig. 2. An example

mechanism to start

to control Home

and stop gesture

Appliances

recognition.

As shown in Fig. 3, Ubi-Finger consists of three sensors to detect gestures of fingers, an infrared transmitter to select a target device in real

Fig. 3.

world and a

Mouse Field

microcomputer to

Although various

control these sensors

interaction

and communicate

technologies for

with a host computer.

handling information

Each sensor

in the ubiquitous

generates the

computing

information of

environment have

motions as follows:

been proposed, some

(1) a bending degree

technologies are too

of the index finger,

simple for performing

(2) tilt angles of the

rich interaction, and

wrist, (3) operations

others require special

of touch sensors by a

expensive

thumb. We use (1)

equipments to be

and (2) for

installed everywhere,

recognition of

and cannot soon be

gestures, and use (3)

available in our

for the trigger

everyday

Page 117 of 216

environment. Here

command to control

there is a new simple

the flow of

and versatile i/p

information.

device called the Mouse Field, which enables users to control various information applications easily without huge amount of cost. A mouse field consists of an ID recognizer and motion sensors that can detect an object and its movement after the object is placed on it. The system can interpret the user’s action as a "Placing"

"Moving"

(detecting an

(detecting its

object)

movement)

Fig. 4. Basic

reader and motion

concept of Mouse

sensing devices into

Field

one package. Fig. 4

Mouse Field is a

shows an

device which

implementation of

combines an ID

Mouse Field, which

Page 118 of 216

consist of two

detects the

motion sensors and

direction and

an RFID reader

rotation of the

hidden under the

object.

surface. The RFID reader and the two optical mouses are connected to a PC through a USB cable, and they can detect the ID and the motion of the object put on the device. When a user puts an object with an RFID on the Mouse Field, it first detects what was kept on the RFID reader. When the use moves or rotates the object, motion sensor Front view

Back View

Fig. 5

Mouse Field and CD

Implementation

jackets which

of a Mouse Field

represent the music

Device.

in the CD. All the

Fig. 5 shows how a

music in the CD is

user can enjoy

saved in a music

music using a

server, and an RFID

Page 119 of 216

tag is attached to each jacket.

Page 120 of 216

These are used to control various parameters without special parameters. Information Hoppers and Smart Posters Once these zones are setup, computers on the network will have some interesting capabilities. The system will help to store and retrieve data in an Information hopper. This is a timeline of information that keeps track of when data is created. The hopper knows who created it, where they were and who they were with. Another application that will come out of this ultrasonic location system is the smart poster. A convention computer interface requires us to click on a button on your computer screen. In this new system, a button can be placed anywhere in your workplace, not just on the computer display. The idea behind smart posters is that a button can be a piece of paper that is printed out and struck on a wall. Smart posters will be used to control any device that is plugged into the network. The poster will know where to send a file and a user’s preferences. Smart posters could also be used in advertising new services. To press a button on a smart poster, a user will simply place his or her bat in the smart poster button and click the bat. The system automatically knows who is pressing the poster’s button. Posters can be created with several buttons on it. Ultrasonic location systems will require us to think outside of the box. Traditionally, we have used our files, and we may back up these files on a network server. This ubiquitous network will enable all computers in a building to transfer ownership and store all our files in a central timeline. Moving towards a future of Ubiquitous Computing We suggest a new method to carry all of your personal media with you in a convenient pocket form factor, and have wireless access to it when standing in front of a PC, kiosk, or large display, anywhere in the world that might significantly improve your mobile computing experience. Intel researchers are developing a new class of mobile device that leverages advances in processing, storage, and communications technologies to provide

ubiquitous access to personal information and applications through the existing fixed infrastructure. The device, called a personal server is a small, lightweight computer with high-density data storage capability. It requires no display, so it can be smaller than a typical PDA. A wireless interface enables the user to access content stored in the device through whatever displays are available in the local environment. For example, in the digital home, the personal server could wirelessly stream audio and video stored on the device to a PC or digital home TV. The technology to enable these scenarios and more is now being explored. Conclusion We are moving toward a future in which computing will be ubiquitous, woven seamlessly into the fabric of everyday life. Researchers are engaged in several projects to explore technologies and usage models for everyday uses of computing. In their research, they are addressing fundamental issues that must be resolved in order to enable “anytime, anywhere” computing. To make ubiquitous computing a reality will require the collaboration of researchers in a broadband of disciplines, within computer science and beyond. Resources  Application Coordination Infrastructure for Ubiquitous Computing Rooms.  Ubiquitous Bio-Information Computing (UBIC 2)  What is Ubiquitous Computing? – Overview and resources.  How Ubiquitous Networking will work? – Kevin Bensor.  Panasonic Center: Realizing a Ubiquitous network society.  Ubiquitous Computing Management Architecture.  Introduction to UC.  UC in Education.  Designing Ubiquitous Computer – Resources.

Research works on UC 

Ichiro Satoh’s Research work on UC.



Bill Schilit’s work on UC.



Matthias Lampe’s work on UC.



Pekka Ala – Siuru’s work on UC.



Louise Barkhuus’ work on UC.



George Roussos’ work on ubiquitous commerce.



Dr. Albrecht Schmidt’s Research work on Ubiquitous Computing.

UC Research  Research in UC and Applications at University of California, Irvine.  Fuego: Future Mobile and Ubiquitous Computing Research.  The Ubiquitous Computing Research Group at the University of Victoria.  Computing Department Research themes – Mobile and Ubiquitous computing.  Research in Ubiquitous Computing.  GGF Ubiquitous Computing Research Group.  Distributed Software Engineering Group Research into Ubiquitous Computing.  Mobile Ubiquitous Security Environment (MUSE).

Bibliography www.ubiq.com www.ubiqcomputing.org www.teco.edu www.personalubicom.com www.searchnetworking.techtarget.com www.gseacademic.harvard.edu www.comp.lancs.as.uk

www.Ice.eng.cam.ac.uk

CRYPTOGRAPHY THE ART OF SECRET WRITING

SRKR ENGINEERING COLLEGE BHIMAVARAM.

PRESENTED BY: B.SUDARSHAN

CH.LAKSHMI SAROJA

Regd.no:660751015

Regd.no:660751036

3rd year CSE

3rd year CSE

[email protected] [email protected]

ABSTRACT The present century has been one of many scientific discoveries and technological advancements. With the advent of technology came the issue of security. As computing systems became more complicated, there was an increasing need for security. This paper deals with cryptography, which is one of the methods to provide security. It is needed to make sure that information is hidden from anyone for whom it is not intended. It involves the use of a cryptographic algorithm used in the encryption and decryption process. It works in combination with the key to encrypt the plain text. Public key cryptography provides a method to involve digital signatures, which provide authentication and data integrity. To simplify this process an improvement is the addition of hash functions. The main focus of this paper is on quantum cryptography, which has the advantage that the exchange of information can be shown to be secure in a very strong sense, without making assumptions about the intractability of certain mathematical problems. It is an approach of securing communications based on certain phenomena of quantum physics. There are two bases to represent data by this method depending on bit values. There are ways of eavesdropping even on this protocol including the Man –in-theMiddle attack. The quantum computers could do some really phenomenal things for cryptography if the practical difficulties can be overcome. Encryption and decryption: Data that can be read and understood without any special measures is called plaintext or clear text. The method of disguising plaintext in such a way as to hide its substance is called encryption. Encrypting plaintext results in unreadable gibberish called cipher text. You use encryption to make sure that information is hidden from anyone for whom it is not intended, even those who can see the encrypted data. The process of reverting ciphertext to

its original plaintext is called decryption.

Figure 1-1. Encryption and decryption

Strong cryptography: Cryptography

can

be

strong

or

weak,

as

explained

above.

Cryptographic strength is measured in the time and resources it would require to recover the plaintext. The result of strong cryptography is ciphertext that is very difficult to decipher without possession of the appropriate decoding tool. How difficult? Given all of today’s computing power and available time—even a billion computers doing a billion checks a second—it is not possible to decipher the result of strong cryptography before the end of the universe. How does cryptography work? A cryptographic algorithm, or cipher, is a mathematical function used in the encryption and decryption process. A cryptographic algorithm works in Combination with a key—a word, number, or phrase—to encrypt the plaintext. The same plaintext encrypts to different ciphertext with different keys. The security of encrypted data is entirely dependent on two things: the strength of the cryptographic algorithm and the secrecy of the key. A cryptographic algorithm, plus all possible keys and all the protocols that make it work, comprise a cryptosystem. PGP is a cryptosystem. Conventional cryptography: In conventional cryptography, also called secret-key or symmetric-key encryption, one key is used both for encryption and decryption. The Data Encryption Standard (DES) is an example of a conventional cryptosystem

that is widely employed by the U.S. government.

Public key cryptography The

problems

of

key

distribution

are

solved

by

public

key

cryptography. Public key cryptography is an asymmetric scheme that uses a pair of keys for encryption: a public key, which encrypts data, and a corresponding private key (secret key) for decryption. It is computationally infeasible to deduce the private key from the public key. Anyone who has a public key can encrypt information but cannot decrypt it.Only the person who has the corresponding private key can decrypt the information.

The primary benefit of public key cryptography is that it allows people who have no preexisting security arrangement to exchange messages securely. The need for sender and receiver to share secret keys via some secure channel is eliminated; all communications involve only public keys, and no private key is ever transmitted or shared. Some examples of publickey cryptosystems are Elgamal, RSA, Diffie-Hellman and DSA, the Digital Signature Algorithm. Keys: A key is a value that works with a cryptographic algorithm to produce a specific ciphertext. Keys are basically really, really, really big numbers. Key size is measured in bits; the number representing a 2048-bit key is huge. In public-key cryptography, the bigger the key, the more secure the ciphertext. However, public key size and conventional cryptography’s secret key size are totally unrelated. A conventional 80-bit key has the equivalent strength of a 1024-bit public key. A conventional 128-bit key is equivalent to a 3000-bit public key. Again, the bigger the key, the more secure, but the algorithms used for each type of cryptography are very different.

While the public and private keys are mathematically related, it’s very difficult to derive the private key given only the public key; however, deriving the private key is always possible given enough time and computing power. This makes it very important to pick keys of the right size; large enough to be secure, but small enough to be applied fairly quickly. Larger keys will be cryptographically secure for a longer period of time. Keys are stored in encrypted form. PGP stores the keys in two files on your hard disk; one for public keys and one for private keys. These files are called keyrings. If you lose your private keyring you will be unable to decrypt any information encrypted to keys on that ring. Digital signatures: A major benefit of public key cryptography is that it provides a method for employing digital signatures. Digital signatures let the recipient of information verify the authenticity of the information’s origin, and also verify that the information was not altered while in transit. Thus, public key digital signatures provide authentication and data integrity. A digital signature also provides non-repudiation, which means that it prevents the sender from claiming that he or she did not actually send the information. These features are every bit as fundamental to cryptography as privacy, if not more. A digital signature serves the same purpose as a handwritten signature. However, a handwritten signature is easy to counterfeit. A digital signature is superior to a handwritten signature in that it is nearly impossible to counterfeit, plus it attests to the contents of the information as well as to the identity of the signer. Some people tend to use signatures more than they use encryption. Instead of encrypting information using someone else’s public key, you encrypt it with your private key. If the information can be decrypted with your public key, then it must have originated with you.

Hash functions: The system described above has some problems. It is slow, and it produces

an enormous volume of data—at least double the size of the

original information. An improvement on the above scheme is the addition of a one-way hash function

in the process. A one-way hash function takes

variable-length input in this case, a message of any length, even thousands or millions of bits—and produces a fixed-length output; say, 160 bits. The hash function ensures that, if the information is changed in any way—even by just one bit—an entirely different output value is produced. PGP uses a cryptographically strong hash function on the plaintext the user is signing. This generates a fixed-length data item known as a message digest. Then PGP uses the digest and the private key to create the “signature.” PGP transmits the signature and the plaintext together. Upon receipt of the message, the recipient uses PGP to recompute the digest, thus verifying the signature. PGP can encrypt the plaintext or not; signing plaintext is useful if some of the recipients are not interested in or capable of verifying the signature. As long as a secure hash function is used, there is no way to take someone’s signature from one document and attach it to another, or to alter a signed message in any way. The slightest change to a signed document will

cause the digital signature verification process to fail. Digital signatures play a major role in authenticating and validating the keys of other PGP users.

QUANTUM CRYPTOGRAPHY - BASIC IDEAS tum • Ability to detect eavesdropping.

•

Detection works only after the information was taken.

•

Usually requires classical information channel for effective communication.

USES OF QUANTUM CRYPTOGRAPHY

•

Primarily used for key exchange for classical cryptography.

•

Key doesn’t have any information value.

•

The receiver knows if any parts of the key are intercepted.

PROTOCOL: BB84

•

The first protocol for Quantum Cryptography.

•

Introduced by Charles H. Bennett from IBM NY and Gilles Brassard from U.S of Montreal in 1984.

•

The protocol uses both classical and quantum channels.

•

There are many variations of this protocol.

DATA REPRESENTATION: Two basis are used:

•

Vertical

•

Diagonal

Depending the bit value the direction on the basis is chosen.

THE EXCHANGE:

•

The Sequence of events:

-

A generates random key and encoding basis.

-

A sends the polarized photons to B.

-

A announces the polarization for each bit.

-

B generates random encoding basis.

-

B measures photons with random basis.

-

B announces which basis are the same as A’s.

•

Finally, the matching bits are used as the key for a classical channel.

•

Privacy amplification is used to generate the final key.

SEQUENTIAL VIEW:

A

B

EAVESDROPPING: Eavesdropping on the quantum channel requires measuring the photons, therefore perturbing the system.

Eavesdropper will be required to resend the photons at random polarization, the receiver will end up with 25% of the key. MAN - IN THE - MIDDLE ATTACK: Requires the attacker to take over both classical and quantum channels.

Can be prevented by authenticating the messages on the classical channel.

ADVANTAGES AND DISADVANTAGES: Conclusion • Based on natural quantum laws

•

Computational Complexity Expires.

•

There is no expiration date on the security of QC messages.

•

Perfect for public communication

•

Easy to detect an eavesdropper.

•

Severally limited by technology

•

Practical systems are limited by distance.

•

Photon emitters and detectors are far from perfect, causing a lot of errors.

•

Most protocols require a classical channel.

QUANTUM CRYPTOGRAPHY – PRACTICALITIES: Progress in quantum optics has resulted in new photon sources, new photo-detectors, and better optical fibers; the components which have the potential for exhibiting the relevant quantum phenomena over much larger distances. This holds out a reasonable prospect for implementation of a secure key distribution system on a large local area network, transmitting at about 20k bits per second with present technology.

REFERENCES: i.

“Cryptography and Network Security, Principles and Practices” (Third Edition)-William Stallings.

ii. Diffie.W and Hellman.M – “Multiuser Cryptography Techniques.” iii. Rivesp.R , Shamir.A and Adleman.L- “A Method for obtaining Digital Signatures and Public Key Cryptographic Systems.”

MOBILE COMPUTING

 Presented by:

K.SANTHOSH. II/IV –B-Tech ID: 06091A0582 [email protected] [email protected] Ph: 9908538218

T.RUPESH ROHITH. II/IV –B-Tech ID: 06091A0577 [email protected] Ph: 9441190808

RAJEEV GANDHI MEMORIAL COLLEGE OF ENGINEERING AND TECHNOLOGY , NANDYAL.

Abstract :

Today’s work force is increasingly mobile, yet the speed at which business operates demands that

mobile workers stay in

constant communication with their customers and colleagues. To provide

them with instant access to enterprise, personal and

Internet information, many corporations are

designing and

deploying ‘Mobile computing’ solutions. These solutions allow corporations to

reap

a significant

return on investment by 1. Increasing worker productivity. 2. Eliminating task duplication. 3. Improving customer service. 4. Providing point of service revenue opportunities. Mobile computing is an entirely new paradigm of

computing

and communication. Mobile users want to use different devices and have information

formed appropriately for each. Hence wireless

solutions need to address the unique needs of mobile workers. Unlike their wired counter parts, design of software for mobile devices must consider

resource

limitation,

battery

Consequently new software and developed.

power

and

display

size.

hardware techniques must be

Holding records on all the latest modifications done in a landmark is very difficult for a stationary record holder. So to overcome this disadvantage mobile record holding came into existence.. In this particular paper we deal with location-based intelligence technology which can provide spatial data & allows the personnel to react & respond to the emergency situations. It ensures homeland security & public safety. we also deal with the map info.. Mobile map info helps the field workers to obtain the critical info on natural calamities. INTRODUCTION : Wireless networking technology has engendered a new era of computing, called

mobile computing. Mobile Computing is an umbrella

term used to describe

technologies that enable people to access network

services any place, anytime, and anywhere. Ubiquitous computing and nomadic computing are synonymous with

mobile computing. Mobile computing helps users to be productive

immediately by reducing

the training requirements associated with

traditional automated data collection methods and provides a higher level of portability than keyboard-based systems. Field-based users can access any information available from the system at any time to make critical business decisions. This information is available at the point of use, wherever and whenever they need it.Portable devices like laptop and palm top computers give mobile

users

access to

diverse sources of global information anywhere and at any time. Wireless refers to the method of transferring information between computing devices, such as

a personal data assistant (PDA), and a data

source, such as an agency database server, without a physical connection.

Not all wireless communications technologies are mobile. For

example,

lasers are used in wireless data transfer between buildings, but cannot be used in mobile communications at this time. Mobile simply describes a computing device that is not restricted to a desktop. A mobile

device may be a PDA, a "smart" cell phone or Web

phone, a laptop computer, or any one of numerous other devices that allow the user to complete computing tasks without being tethered, or connected, to a network. Mobile computing does not necessarily require wireless communication. In fact, it may not require communication between devices at all. Mobile devices Here we have seven different types of mobile devices:

Laptop

computers ,PDA’s, handheld PCs Pagers, Smartphones, cellular phones, bar code scanners, Blue tooth etc..; Challenges in mobile computing Wireless and mobile environments bring different challenges to users and service providers

when compared to fixed, wired networks. Physical

constraints become much more important,

such as device weight, battery

power, screen size, portability, quality of radio transmission, error rates. The major challenges in mobile computing are described including: low

bandwidth, high error rate, power restrictions,

security, limited

capabilities, disconnection and problems due to client mobility. Security Security and privacy are of specific concerns in wireless communication because of the ease of connecting to the wireless link anonymously. Common problems are impersonation, denial of service and tapping. The main technique used is encryption. In personal profiles of users

are used to restrict access to the mobile units. INFRASTRUCTURE, PRODUCTS & SERVICES MapInfo Government Grant Program Aids Homeland Security ….. MapInfo Corporation has announced its Government Grant Program to assist

communities

with

a

population

of

less

than

150,000

in

the

development and deployment of homeland security and continuity initiatives. The company’s location-based intelligence technology will enable spatial data on the Internet to be shared across departments, such as public works, public utilities, police and fire departments, allowing personnel to immediately react and respond to emergency situations. Field workers equipped with a laptop or handheld device will be able to exchange critical location information regarding flood areas, storm patterns, earthquake regions and homeland security practices. MapInfo software easily integrates with a municipality’s existing IT infrastructure, eliminating the need for additional technology investments. Both internal and external databases can be accessed with MapInfo, so multiple government organizations can share data in different formats. With the ability to convert any address or landmark into a point on a map,

MapInfo’s

homeland

security

solutions

enable

government

organizations to make better-informed decisions to protect their citizens and assets, the company said. To qualify, municipalities must submit a homeland security, public safety or continuity government plan for the use of MapInfo software, including:

 MapInfo

Professional, a location-intelligence solution for

performing advanced and detailed data analysis and data creation to plan logistics and prepare for emergency response.  MapInfo Discovery, an enterprise-wide solution that enables

users to share interactive location analysis reports and maps via the Internet or intranet.  MapInfo StreetPro Display County, a database that contains

addressed street segments for up-to-date analysis and timely emergency response practices.  MapInfo MapMarker Plus County, a geocoding engine that

adds geographic coordinates to every record in a database, enabling users to map, analyze and share homeland security data. RECENT APPLICATIONS : Mobile computers are also characterised as ubiquitous computers. Ubiquity is the quality or state of being everywhere. Some of the uses for the mobile computers can be:



For Estate Agents Estate agents can work either at home or out in the field. With mobile computers they can be more productive. They can obtain current real estate information by accessing multiple listing services, which they can do from home, office or car when out with clients. They can provide clients with immediate feedback regarding specific homes or neighborhoods, and with faster loan approvals, since applications can be submitted on the spot. Therefore, mobile computers allow them to devote more time to clients.



In courts Defense counsels can take mobile computers in court. When the opposing counsel references a case which they are not familiar, they can use the computer to get direct, real-time access to on-line legal database services, where they can gather information on the case and related precedents. Therefore mobile computers allow immediate access to a wealth of information, making people better informed and prepared.



In companies Managers

can

use

mobile

computers

in,

say,

critical

presentations to major customers. They can access the latest market share information. At a small recess, they can revise the presentation to take advantage of this information. They can communicate with the office about possible new offers and call meetings for discussing responds to the new proposals. Therefore, mobile computers can leverage competitive advantages. 

Government: Applications center around assessments, inspections, and work orders. Most of these applications involve auditing some sort of facility or process

(food service, restaurant, nursing home, child

care, schools, commercial and residential buildings).



Healthcare: The focus in this industry has been on automating patient records, medication dispension, and sample collection. A common goal is to leverage

mobile computing in the implementation of

positive patient identification.

Uses like the above are endless. People find one that serves their needs so more and more are subscribing for mobile computers. NEW ERA : Mobile computers are something like the opposite to virtual reality. Where virtual reality puts people inside a computer-generated world, mobile computing forces the computer to live out here in the world with people. THE FUTURE: With rapid technological advancements in Artificial Intelligence (AI), Integrated

Circuitry and increases in computer processing

speeds, the future of mobile computing

looks increasingly exciting.

First phase started with large main frames -shared by many users, and then came the personal computers that allowed single user processing tasks and

now the trend is of mobile computers,

where a single user can use many computers. Use of AI may allow mobile units to be ultimate in personal secretaries, which can

receive emails and paging messages,

understand what they are about and change the individual’s personal schedule according to the message. The individual to plan his/her day can then use this.

The introduction of 3G and other advanced technologies will lead to many

applications, which are easily accessible and easy to use.

Mobile Computing is an emerging technology with most promising features like high speed data transfers, availability and accessibility of data from remote locations… Etc.

CONCLUSION: In this paper, we briefly described some of the most important technologies for

Mobile Computing. Mainly the map

information that is described in this context is a milestone in the present packed world. WAP will take a major role in future mobile applications. We need to

develop technologies that suite for mobile

devices by considering factors like resource limitation,

bandwidth

availability and accessibility problems. Requirements need to be reviewed and studied very carefully by all the involved actors. Our analysis, as presented in this paper, shows

that the

technologies and issues involved in mobile computing deployment and provision cover a very

wide spectrum including operating system

capabilities, user interface design, positioning

techniques, terminal

technologies, network capabilities, etc. The meticulous mapping of these technical aspects to the identified

requirements

is

a

critical

success

factor

for

Computing. Stay tuned … mobile computing is the way the world is heading. REFERENCE: Interview with Mr Eleftherios Koudounas, Assistant Commercial Services Manager at Cyprus Telecommunications Authority Interview with Dr Leonidas Leonidou, Mobile Services, Cyprus Telecommunications Authority Interview with Dr Zinonas Ioannou, Mobile Services, Cyprus Telecommunications Authority

Mobile

Cellular Communications for Data Transmission M Flack & M Gronow Visions of a cellular future http://www.ericsson.se/EPI/BR-vision.html An overview of cellular techology http://www.ericsson.se/EPI/BR-overview.html The CDPD Network John Gallant, Technical Editor, PCSI

************************************************************* ************************************************************* ************************************************************* ************************************************************* ************************

BIOMETRICS FOR FOOL PROOF SECURITY

Submitted by

M.AVINASH

M.CHIRANJEEVI

Roll.No.660751011

Roll.No.660751017

3rd year CSE

3rd year CSE

[email protected] [email protected]

FROM S.R.K.R COLLEGE OF ENGINEERING BHIMAVARAM, W.G (dist.) ANDHRA PRADESH

ABSTRACT Now-a-days we are facing majority of crimes related to security issues and these arise due to the leakage of passwords or illegal authentication.

At

one

end,

there

is

a

continuous

and

tremendous

improvement in the lifestyle of Humans while at the other end; the technological crimes are increasing rapidly. As there is a problem, there must be a solution. The need for a compromising technology which can be adopted is highly imperative. Technologies capable of identifying each person uniquely need to be developed. The only powerful solution for the problem of illegal authentication is Biometrics. This paper provides an overall idea of Biometrics , the typical Biometric Model, an overview of the Biometric techniques and focuses mainly on Keystroke Biometrics which is easy to implement and can provide fool proof security based on the effectiveness of the algorithm.

INTRODUCTION: As per the saying “NECESSITY IS THE MOTHER OF INVENTION”, the need for a new type of identification and authentication technique has led to the development of Biometrics. “Biometrics is an automated method of recognizing a person based on a physiological or behavioral characteristic. “ Biometric-based solutions are able to provide for confidential financial transactions and personal data privacy. Most systems make use of a personal identification code in order to authenticate the user. In these systems, the possibility of malicious user gaining access to the code cannot be ruled out. However, combining the personal identification code with biometrics provides for robust user authentication system. Biometrics is of two kinds: One deals with the physical traits of the user (Retinal scanning, Fingerprint scanning, DNA testing etc.,) and the other deals with the behavioral traits of the user (Voice recognition, Keystroke dynamics, etc.) .Utilized alone or integrated with other technologies such as smart cards, encryption keys and digital

signatures, biometrics is set to pervade nearly

all aspects of the economy and our daily lives. THE BIOMETRIC MODEL: The biometric authentication system consists: User interface or the biometric reader, Communication Subsystem, The Controlling software, Data storage. Matching Score

95% Data Collection Biometric Capture

Decision Making

Template Extraction

Verification

Signal Processin g

Enrollment Storage

BIOMETRIC MODEL

Biometric system works by taking a number of samples of physiological or behavioral characteristics to produce a reliable template of the user information. The user is verified against a template in the memory, which he claims to be himself and the user is authenticated if the biometric pattern of the user matches with the template. The biometric sample of the person is not stored in the host computer or the controller. So there is no possibility of the others getting it. Moreover, the biometric template of person is stored in the form of a dynamic binary template with suitable encryption to provide utmost security BIOMETRIC TECHNIQUES:

 Fingerprint Verification: This is one of the oldest forms of biometric techniques which involves mapping of the pattern of the fingerprint of the individual and then comparing the ridges, furrows, within the template. The fingerprint given to the device is first searched at the coarse level in the database and then finer comparisons are made to get the result.

 Iris Recognition: In Iris and Retinal scanning, the iris and the retina are scanned by a low intensity light source and the image is compared with the stored patterns in the database template. They are the fastest and the secure form of biometry.

 Facial Scanning: Facial scanning involves scanning of the entire face and checking of critical points and areas in the face with the template. This method is not completely reliable and so it is used in association with another biometric technique.

 Hand and Finger geometry: This method uses the data such as length, shape, distance between the fingers, overall dimensions of the hand and also the relative angle between the fingers. Modern systems use this technique in association with the Fingerprint scanning technique.

 Voice Biometry: It is proved that the frequency, stress and accent of speech differ from person to person. Voice biometry uses this concept to solve the problem of illegal user.

 Signature Verification: This technology uses the dynamic analysis of a signature to authenticate a person. This technology is based on measuring speed, pressure and angle used by the person when a signature is produced.

 Keystroke dynamic: In this technique, the system analyses the rhythm of typing the password. KEYSTROKE BIOMETRICS: “The keystroke biometrics makes use of the inter-stroke gap that exists between consecutive characters of the user identification code.” When a user types his authentication code, there exists a particular rhythm or fashion in typing the code. If there does not exist any abrupt change in this rhythmic manner, this uniqueness can be used as an additional security constraint. It has been proved experimentally that the manner of typing the same code varies from user to user. Thus this can be used as a suitable biometric. Further, if the user knows before hand about the existence of this mechanism, he can intentionally introduce the rhythm to suite his needs. IMPLEMENTATION DETAILS: As the user logs onto the system for the first time, a database entry is created for the user. He is then put through a training period, which consists of 15-20 iterations. During this time, one obtains the inter-stroke timings of

all the keys of the identification code. The inter stroke interval between the keys is measured in milliseconds. The systems’ delay routine can be used to serve the purpose. The delay routine measures in milliseconds and the amount of delay incurred between successive strokes can be used as a counter to record this time interval. The mean and standard deviation of the code are calculated. This is done in order to provide some leverage to the user typing the code. The reference level that we chose is the mean of the training period and the rounded standard deviation is used as the leverage allotted per user. These values are fed into the database of the user. These details can also be incorporated onto the system’s password files in order to save the additional overhead incurred. The mean and the standard deviation can be determined by using the relationship given below. Mean= (1/n)

Standard deviation=

x (i)

{[ (X (i)-mean)] 2/n}

Once the database entry has been allotted for the user, this can be used in all further references to the user. The next time the user tries to login, one would obtain the entered inter-stroke timing along with the password. A combination of all these metrics is used as a security check of the user. The algorithm given below gives the details of obtaining the authorization for a particular user. The algorithm assumes that the database already exists in the system and one has a system delay routine available PERFORMANCE MEASURES: While considering any system for authenticity, one needs to consider the false acceptance rate (FAR) and the false rejection rate (FRR). The [FAR] is the percentage of unauthorized users accepted by the system.

The [FRR] is the percentage of authorized users not accepted by the system. An increase in one of these metrics decreases the other and vice versa. The level of error must be controlled in the authentication system by the use of a suitable threshold such that only the required users are selected and the others who are not authorized are rejected by the system. In this paper, standard deviation of the user’s training period entry is used as a threshold. The correct establishment of the threshold is important since too strong a threshold would lead to a lot of difficulty in entry even for the legal user, while a lax threshold would allow non-authorized entry. Thus a balance would have to be established taking both the factors into consideration ALGORITHM Input

: User name, User_id, Password.

Output: Registration of a new user (or) Acceptance of a user if registered (or) Rejection of an unregistered user. main () { if (User==New) { read (User); // Getting User name, User_id, Password read (Inter-stroke gap); // Time interval between consecutive characters Add user (database); // Add the User to the database User count =1; } else if (User==Training) { read (User); read (Inter-stroke gap); if (Check (User, Password)) { if (User count<15) { update ( User count); // User count = User count +1 add (Inter-stroke gap); } else if (User count ==15) { update (User count); add (Inter-stroke gap);

Calculate Mean (M), Standard deviation (S.D);

}

} } else if (User==Existing) { read (User); read (deviation); if (Check (User, Password, deviation)) Login; else exit(0); } } Analysis of inter-keystroke timing of user code: A graph is plotted between keystrokes and keystroke timing. The ‘X’ axis indicates the number of inter-keystrokes and negative ‘Y’ axis indicates the inter-keystrokes timing in milliseconds. User accepted: Graph I shows the inter-keystroke timing analysis when the user is accepted. Here it can be easily seen that when the user is authentic or when he types in his normal rhythm, the user automatically comes into the predefined ranges. The current inter-keystroke timing lies around the database inter-keystroke timing, thereby providing adequate amount of predefined ranges. FAR and FRR can be to a treat extent so that only db=Database Graph I: reduced Inter keystroke timing analysis when the user gets access to the system. The +R boundary and –R the legal +R=+VE Boundary user accepted boundary give the desired range so that onlyisthe legal user gets access. -R=-VE Boundary In the graph, the line (L3) indicates the current pattern of typing the access c=Current -R -R code on the keyboard; the line (L2) indicates the keystroke pattern -R

-R

-R

c c according to reference level and the line (L1) and (L2) indicates the -R

-R

db

db

-R (L1)

c

db (L2) c (L3)

positive c c and the negative ranges. db db The ranges dbcan be decided by the standard db

c

c

deviation method, which is used here for analysis or any other adaptive c

db +R method. +R

db

+R

+R

+R +R

+R

ACCESS GRANTED

User not accepted:

c

+R +R (L4)

Graph II indicates inter-keystroke timing when the user is not legal or not following his rhythmic behavior of typing the access code. It can be easily noticed when the user is not legal, his typing pattern for the access code is not at all into the predefined ranges.

db=Database user is +R=+VE Boundary rhythmic -R=-VE Boundary c=Current

Graph II: Inter keystroke timing when the not legal or not following his behaviour

-R

-R

-R -R

-R -R

-R

db

c db c

db

db

db

-R (L1)

db db c

db

db +R

c c

+R

+R +R

A MULTIMODAL BIOMETRIC SYSTEM: +R +R

(L2)

+R +R +R (L4)

c c A biometric system which relies only on a single c biometric (L3)

ACCESS DENIED identifier is often not able to meet the desired performance requirements.

Identification based on multiple biometrics represents an emerging trend. This system takes the advantage of the capabilities of each individual biometric and overcomes the limitations of individual biometric. This multi biometric system operates with an admissible response time.

EXAMPLE (A Multibiometric system): (FINGER PRINT + FACIAL SCANNING + SPEECH)

Face Extractor

Databas e Browser

Minutiae Extractor

Ceptral Analysis

FACIAL SCANNING Template Database

Face Locator

FINGERPRINT

SPEECH ACQUISITION MODULE

Eigenspace Projection And HMM training

Eigenspace Comparison

Minutiae Extractor

Minutiae matching

Ceptral Analyzer

HMM scoring

Decision Fusion

Accept/ Reject

VERIFICATION MODULE APPLICATIONS: BIOMETRIC BANKING: Banks have been experimenting with keystroke Biometrics for ATM machine use and to counteract the credit card frauds. The smart card or the credit card may be incorporated with the biometric information. When a user inserts his card for verification, the biometric sample of the person can be verified precisely and if it is identical the person is authenticated. The advantage of this system is that the user can enjoy the facilities offered by the Bank along with utmost security. INTERNET SECURITY: If the password is leaked out, the computer or the web server will not be able to identify whether the original user is operating the computer. PCs fitted with biometric sensors can sense the biometric template and transmit it to the remote computer so that the remote server is sure about the user in the computer. BIOMETRIC SMART CARDS: Biometric technologies are used with smart cards for ID systems applications specifically due to their ability to identify people with minimal ambiguity. A biometric based ID allows for the verification of “who you claim to be” (information about the card holder stored in the card) based on “who you are” (the biometric information stored in the smart card), instead of, or possibly in addition to, checking “what you know” (such as password). CONSTRAINTS IN KEYSTROKE BIOMETRICS: A question that arises with any technology is that “Does this technology have any constraints?” The answer to this question is that, “It purely depends upon its implementation mechanism”. In Keystroke biometrics, the person being authenticated must have registered their bio-identity before it can be authenticated. Registration processes can be extremely complicated and very inconvenient for users.

This is

particularly true if the user being registered is not familiar with what is happening. The problem for the operator is that the right person will be rejected occasionally by what

might be presented as a ‘foolproof’ system. Both the FAR and the FRR depend to some extent on the deviation allowed from the reference level and on the number of characters in the identification code (Password). It has been observed that providing a small deviation lowers the FAR to almost NIL but at the same time tends to increase the FRR. This is due to the fact that the typing rhythm of the user depends to some extent on the mental state of the user. So, a balance would have to be established taking both the factors into consideration. SOLUTION: The performance measure of Keystroke biometrics purely depends on User psychology, i.e., the user’s particular temperament; understanding and current state of mind can have a dramatic impact on real system performance. If a user is not happy about using the biometric device, he is likely to be consistent in using it, potentially producing a much larger than average error rate. Conversely, if a user is intrigued and enthusiastic about using the device, he is likely to use it as intended, be more consistent and enjoy 8relatively low error rates. Since this is the case, clearly we should aim for well educated (in terms of the system) users who have good quality reference templates and are happy with the overall system concept and its benefits. CONCLUSION: Keystroke Biometrics offers a valuable approach to current security technologies that make it far harder for fraud to take place by preventing ready impersonation of the authorized user. Even if the unauthorized user discovers the access code, he cannot get access to the system until and unless he also knows the rhythm. Also, the typing rhythm can be self-tuned by the user to suit his needs. As the keyboard has duplicate keys, the typing rhythm also depends whether the user is a left-handed person or a right-handed person. Positively Keystroke Biometrics will replace the entire traditional security systems in the future.

References: [1] S.Singh, “The Code Book”, Doubleday, 1999. [2] Exploring Biometrics: Seeing the Unseen A paper By Neil F.Johnson Sushil Jajodia George Mason University

JNTU COLLEGE OF ENGINEERING ANANTAPUR (AUTONOMOUS)

Presented by --K.Balanjaneyulu (05001A0540) ph: 9966645162

S.Vijay Raghavendra (05001A0539)

Email id: [email protected] [email protected]

Abstract:

Find where your kids have been! Verify employee driving routes! Review family members driving habits! Watch large shipment routes! Know where anything or anyone has been! All this can be done merely by sitting at your own desk! Finding your way across the land is an ancient art and science. The stars, the compass, and good memory for landmarks helped you get from here to there. Even advice from someone along the way came into play. But, landmarks change, stars shift position, and compasses are affected by magnets and weather. And if you've ever sought directions from a local, you know it can just add to the confusion. The situation has never been perfect. This has led to the search of new technologies all over the world .The outcome is THE GLOBAL POSITIONING SYSTEM. Focusing the application and usefulness of the GPS over the age-old challenge of finding the routes, this paper describes about the Global Positioning System, starting with the introduction, basic idea and applications of the GPS in real world. Introduction: The Global Positioning System (GPS) is a worldwide radio-navigation system formed from a constellation of 24 satellites and their ground stations. Global Positioning Systems (GPS) are space-based radio positioning systems that provide 24 hour three-dimensional position, velocity and time information to suitably equipped users anywhere on or near the surface of the Earth (and sometimes off the earth). Global Navigation Satellite Systems (GNSS) are extended GPS systems, providing users with sufficient accuracy and integrity information to be useable for critical navigation applications. The NAVSTAR system, operated by the U.S. Department of Defense, is the first GPS system widely available to civilian users. The Russian GPS system, GLONASS, is similar in operation and may prove complimentary to the NAVSTAR system. These systems promise radical improvements to many systems that impact all people. By combining GPS with current and future computer mapping techniques, we will be better able to identify and manage our natural resources. Intelligent vehicle location and

navigation systems will let us avoid congested freeways and find more efficient routes to our destinations, saving millions of dollars in gasoline and tons of air pollution. Travel aboard ships and aircraft will be safer in all weather conditions. Businesses with large amounts of outside plant (railroads, utilities) will be able to manage their resources more efficiently, reducing consumer costs. However, before all these changes can take place, people have to know what GPS can do. What it does? GPS uses the "man-made stars" as reference points to calculate positions accurate to a matter of meters. In fact, with advanced forms of GPS you can make measurements to better than a centimeter! In a sense it's like giving every square meter on the planet a unique address. GPS receivers have been miniaturized to just a few integrated circuits and so are becoming very economical. And that makes the technology accessible to virtually everyone. These days GPS is finding its way into cars, boats, planes, construction equipment, movie making gear, farm machinery, even laptop computers. Soon GPS will become almost as basic as the telephone. How GPS works Each satellite is equipped with a computer, an atomic clock and a radio. They enable the satellite to continuously monitor and broadcast its changing position and time. The satellite reports daily to Earth and figures its own position by knowing the distance from the satellite to the user. The GPS receiver on Earth determines its own position by communicating with a satellite. The results are provided in longitude and latitude. If the receiver is equipped with a computer that has a map, the position will be shown on the map. If you are moving, a receiver may also tell you your speed, direction of travel and estimated time of arrival at a destination. Here's how GPS works in five logical steps:

1. The basis of GPS is "triangulation" from satellites.

2. To "triangulate," a GPS receiver measures distance using the travel time of radio signals. 3. To measure travel time, GPS needs very accurate timing which it achieves with some tricks. 4. Along with distance, you need to know exactly where the satellites are in space. High orbits and careful monitoring are the secret. 5. Finally you must correct for any delays the signal experiences as it travels through the atmosphere. Improbable as it may seem, the whole idea behind GPS is to use satellites in space as reference points for locations here on earth. That's right, by very, very accurately measuring our distance from three satellites we can "triangulate" our position anywhere on earth. The Big Idea Geometrically: Suppose we measure our distance from a satellite and find it to be 11,000 miles.Knowing that we're 11,000 miles from a particular satellite narrows down all the possible locations we could be in the whole universe to the surface of a sphere that is centered on this satellite and has a radius of 11,000 miles. Next, say we measure our distance to a second satellite and find out that it's 12,000 miles away. That tells us that we're not only on the first sphere but we're also on a sphere that's 12,000 miles from the second satellite. Or in other words, we're somewhere on the circle where these two spheres intersect.If we then make a measurement from a third satellite and find that we're 13,000 miles from that one, which narrows our position down even further, to the two points where the 13,000 mile sphere cuts through the circle that's the intersection of the first two spheres. So by ranging from three satellites we can narrow our position to just two points in space.To decide which one is our true location we could make a fourth measurement. But usually one of the two points is a ridiculous answer (either too far from Earth or moving at an impossible velocity) and can be rejected without a measurement.

But how can you measure the distance to something that's floating around in space? We do it by timing how long it takes for a signal sent from the satellite to arrive at our receiver. The Big Idea Mathematically In a sense, the whole thing boils down to those "velocity times travel time" math problems we did in high school. Remember the old: "If a car goes 60 miles per hour for two hours, how far does it travel?" Velocity (60 mph) x Time (2 hours) = Distance (120 miles) In the case of GPS we're measuring a radio signal so the velocity is going to be the speed of light or roughly 186,000 miles per second. The problem is measuring the travel time. The timing problem is tricky. First, the times are going to be awfully short. If a satellite were right overhead the travel time would be something like 0.06 seconds. So we're going to need some really precise clocks. But assuming we have precise clocks, how do we measure travel time? To explain it let's use a goofy analogy: Suppose there was a way to get both the satellite and the receiver to start playing "The Star Spangled Banner" at precisely 12 noon. If sound could reach us from space (which, of course, is ridiculous) then standing at the receiver we'd hear two versions of the Star Spangled Banner, one from our receiver and one from the satellite. These two versions would be out of sync. The version coming from the satellite would be a little delayed because it had to travel more than 11,000 miles. If we wanted to see just how delayed the satellite's version was, we could start delaying the receiver's version until they fell into perfect sync. The amount we have to shift back the receiver's version is equal to the travel time of the satellite's version. So we just multiply that time times the speed of light and BINGO! We’ve got our distance to the satellite.

That's basically how GPS works. Only instead of the Star Spangled Banner the satellites and receivers use something called a "Pseudo Random Code" - which is probably easier to sing than the Star Spangled Banner. A Random Code? The Pseudo Random Code (PRC, shown below) is a fundamental part of GPS. Physically it's just a very complicated

digital

code,

or

in

other

words,

a

complicatedsequence of "on" and "off" pulses as shown here: The signal is so complicated that it almost looks like random electrical noise. Hence the name "Pseudo-Random." There are several good reasons for that complexity: First, the complex pattern helps make sure that the receiver doesn't accidentally sync up to some other signal. The patterns are so complex that it's highly unlikely that a stray signal will have exactly the same shape. Since each satellite has its own unique Pseudo-Random Code this complexity also guarantees that the receiver won't accidentally pick up another satellite's signal. So all the satellites can use the same frequency without jamming each other. And it makes it more difficult for a hostile force to jam the system. In fact the Pseudo Random Code gives the DoD a way to control access to the system. But there's another reason for the complexity of the Pseudo Random Code, a reason that's crucial to making GPS economical. The codes make it possible to use "information theory" to "amplify" the GPS signal. And that's why GPS receivers don't need big satellite dishes to receive the GPS signals. Goofy Star-Spangled Banner analogy assumes that we can guarantee that both the satellite and the receiver start generating their codes at exactly the same time. But how do we make sure everybody is perfectly synced?

If measuring the travel time of a radio signal is the key to GPS, then our stop watches had better be darn good, because if their timing is off by just a thousandth of a second, at the speed of light, that translates into almost 200 miles of error! On the satellite side, timing is almost perfect because they have incredibly precise atomic clocks on board. But what about our receivers here on the ground? Both the satellite and the receiver need to be able to precisely synchronize their pseudo-random codes to make the system work. If our receivers needed atomic clocks (which cost upwards of $50K to $100K) GPS would be a lame duck technology. Nobody could afford it. Luckily the designers of GPS came up with a brilliant little trick that lets us get by with much less accurate clocks in our receivers. This trick is one of the key elements of GPS and as an added side benefit it means that every GPS receiver is essentially an atomicaccuracy clock. The secret to perfect timing is to make an extra satellite measurement. That's right, if three perfect measurements can locate a point in 3-dimensional space, then four imperfect measurements can do the same thing. This idea is fundamental to the working of GPS Extra Measurement Cures Timing Offset If our receiver's clocks were perfect, then all our satellite ranges would intersect at a single point (which is our position). But with imperfect clocks, a fourth measurement, done as a cross-check, will NOT intersect with the first three. So the receiver's computer says "Uh-oh! there is a discrepancy in my measurements. I must not be perfectly synced with universal time." Since any offset from universal time will affect all of our measurements, the receiver looks for a single correction factor that it can

subtract from all its timing measurements that would cause them all to intersect at a single point. That correction brings the receiver's clock back into sync with universal time, and bingo! - you've got atomic accuracy time right in the palm of your hand. Once it has that correction it applies to all the rest of its measurements and now we've got precise positioning. One consequence of this principle is that any decent GPS receiver will need to have at least four channels so that it can make the four measurements simultaneously. With the pseudo-random code as a rock solid timing sync pulse, and this extra measurement trick to get us perfectly synced to universal time, we have got everything we need to measure our distance to a satellite in space. But for the triangulation to work we not only need to know distance, we also need to know exactly where the satellites are. But how do we know exactly where they are? After all they're floating around 11,000 miles up in space. A high satellite gathers no moss That 11,000 mile altitude is actually a benefit in this case, because something that high is well clear of the atmosphere. And that means it will orbit according to very simple mathematics. The Air Force has injected each GPS satellite into a very precise orbit, according to the GPS master plan.On the ground all GPS receivers have an almanac programmed into their computers that tells them where in the sky each satellite is, moment by moment. The basic orbits are quite exact but just to make things perfect the GPS satellites are constantly monitored by the Department of Defense. They use very precise radar to check each satellite's exact altitude, position and speed. The errors they're checking for are called "ephemeris errors" because they affect the satellite's orbit or "ephemeris." These errors are caused by gravitational pulls from the moon and sun

and by the pressure of solar radiation on the satellites. The errors are usually very slight but if you want great accuracy they must be taken into account. Getting the message out Once the DoD has measured a satellite's exact position, they relay that information back up to the satellite itself. The satellite then includes this new corrected position information in the timing signals it's broadcasting. So a GPS signal is more than just pseudo-random code for timing purposes. It also contains a navigation message with ephemeris information as well. With perfect timing and the satellite's exact position you'd think we'd be ready to make perfect position calculations. But there's trouble afoot.

Up to now we've been treating the calculations that go into GPS very abstractly, as if the whole thing were happening in a vacuum. But in the real world there are lots of things that can happen to a GPS signal that will make its life less than mathematically perfect. To get the most out of the system, a good GPS receiver needs to take a wide variety of possible errors into account. Here's what they've got to deal with. First, one of the basic assumptions we've been using throughout this paper is not exactly true. We've been saying that you calculate distance to a satellite by multiplying a signal's travel time by the speed of light. But the speed of light is only constant in a vacuum. As a GPS signal passes through the charged particles of the ionosphere and then through the water vapor in the troposphere it gets slowed down a bit, and this creates the same kind of error as bad clocks. There are a couple of ways to minimize this kind of error. For one thing we can predict what a typical delay might be on a typical day. This is called modeling and it helps but, of course, atmospheric conditions are rarely exactly typical.

Another way to get a handle on these atmosphere-induced errors is to compare the relative speeds of two different signals. This "dual frequency" measurement is very sophisticated and is only possible with advanced receivers. Trouble for the GPS signal doesn't end when it gets down to the ground. The signal may bounce off various local obstructions before it gets to our receiver. This is called multipath error and is similar to the ghosting you might see on a TV. Good receivers use sophisticated signal rejection techniques to minimize this problem. Problems at the satellite Even though the satellites are very sophisticated they do account for some tiny errors in the system. The atomic clocks they use are very, very precise but they're not perfect. Minute discrepancies can occur, and these translate into travel time measurement errors. And even though the satellites positions are constantly monitored, they can't be watched every second. So slight position or "ephemeris" errors can sneak in between monitoring times. Basic geometry itself can magnify these other errors with a principle called "Geometric Dilution of Precision" or GDOP. It sounds complicated but the principle is quite simple. There are usually more satellites available than a receiver needs to fix a position, so the receiver picks a few and ignores the rest. If it picks satellites that are close together in the sky the intersecting circles that define a position will cross at very shallow angles. That increases the gray area or error margin around a position. If it picks satellites that are widely separated the circles intersect at almost right angles and that minimizes the error region. Good receivers determine which satellites will give the lowest GDOP GPS technology has matured into a resource that goes far beyond its original design goals. These days scientists, sportsmen, farmers, soldiers, pilots, surveyors, hikers, delivery drivers, sailors, dispatchers, lumberjacks, fire-fighters, and people from many other walks of life are using GPS in ways that make their work more productive, safer, and sometimes even easier.

Applications: In this section you will see a few examples of real-world applications of GPS. These applications fall into five broad categories. •

Location - determining a basic position

•

Navigation - getting from one location to another

•

Tracking - monitoring the movement of people and things

•

Mapping - creating maps of the world

•

Timing - bringing precise timing to the world

An application of the GPS--Track Stick: What is TrackStick? Simply put, the Track-Stick is a Personal GPS - Global Positioning System with a USB Interface! The GPS Track Stick records its own location, time, date, speed, heading and altitude at preset intervals. With over 1Mb of memory, it can store months of travel information. All recorded history can be outputted to the following formats: RTF ( text file with .html map links) XLS (Microsoft Excel spread sheets) HTML (Webpage with graphics maps) KML (Proprietary Google Earth file) Track Stick works around the planet! The Track Stick GPS Systems outputs .KML files for compatibility with Google Earth. By exporting to Google Earth's .KML file format, each travel location can be pinpointed using 3D mapping technology.

View 3D images of actual recordings of the Track Stick revealing where it has been. Track Stick comes with it's own HTML GPS Tracking Software

Map Location histories can also be exported to the following maps: www.virtualearth.com maps.google.com Microsoft Streets and Trips Encarta... and many other third party mapping programs. www.mapquest.com

How it works The Track Stick receives GPS signals from twenty four satellites orbiting the earth. With this information, the Track Stick GPS systems can precisely calculate its own position anywhere

on

the

planet

to

within

fifteen

meters.

Where it works The Track Stick will work anywhere on the planet Earth! Using the latest in GPS systems mapping technologies, your exact location can be shown on graphical maps and 3D satellite images. The Track Stick's micro computer contains special mathematical algorithms, that can calculate how long you have been indoors. While visiting family, friends or even shopping, the Track Stick can accurately

time and map each and every place you have been. Global positioning System for home or business has never been so easy!

The screenshots below are examples of exactly how the Track Stick Global positioning System will reveal where it has been.

Freeway

Middle East

Cabo San Lucas

Hollywood, CA

Italy

North Pole

Sydney, Australia

Shopping Mall

Conclusion: To conclude, we hereby say that the Global Positioning System is improving day by day. It is the simplest way of replacing the traditional way of finding routes with the new technology. This is surely a striking issue and let’s hopes for the best of it in coming years. References: www.google.co.in www.computerworld.com www.gpsworld.com www.mapquest.com

BY M.SINDHURI B.TECH(COMPUTER SCIENCE) RAJEEV GANDHI MEMORIAL COLLEGE OF ENGG & TECH. NANDYAL-518501. EMAIL ID:[email protected]. J.SUJITHA B.TECH(COMPUTER SCIENCE) RAJEEV GANDHI MEMORIAL COLLEGE OF ENGG & TECH. NANDYAL-518501. EMAIL ID:[email protected].

Abstract

Grid computing, emerging as a new paradigm for next-generation computing, enables

the

sharing,

selection,

and

aggregation

of

geographically

distributed

heterogeneous resources for solving large-scale problems in science, engineering, and commerce.

The

resources

in

the

Grid

are

heterogeneous

and

geographically

distributed. Availability, usage and cost policies vary depending on the particular user, time, priorities and goals. It enables the regulation of supply and demand for resources. It provides an incentive for resource owners to participate in the Grid; and motivates the users to trade-off between deadline, budget, and the required level of quality of service. The thesis demonstrates the capability of economic-based systems for wide-area parallel and distributed computing by developing users’ quality-of-service requirements-based scheduling strategies, algorithms, and systems. It demonstrates their effectiveness by performing scheduling experiments on the World-Wide Grid for solving parameter sweep—task and data parallel—applications. This paper focuses on introduction, grid definition and its evolution. It covers about grid characteristics, types of grids and an example describing a community grid model. It gives an overview of grid tools, various components, advantages followed by conclusion and bibliography.

INTRODUCTION

The Grid unites servers and storage into a single system that acts as a single computer - all your applications tap into all your computing power. Hardware resources are fully utilized and spikes in demand are met with ease. This Web site sponsored by Oracle brings you the resources you need to evaluate your organization's adoption of grid technologies. The Grid is ready when you are.

THE GRID The Grid is the computing and data management infrastructure that will provide the electronic underpinning for a global society in business, government, research, science and entertainment, integrate networking, communication, computation and information to provide a virtual platform for computation and data management in the same way that the Internet integrates resources to form a virtual platform for information. The Grid is the computing and data management infrastructure that will provide the electronic. Grid infrastructure will provide us with the ability to dynamically link together resources as an ensemble to support the execution of large-scale, resource-intensive, and distributed applications. Grid is a type of parallel and distributed system that enables the sharing, selection, and aggregation of geographically distributed "autonomous" resources dynamically at runtime depending on their availability, capability, performance, cost, and users'

quality-of-service requirements.

BEGINNINGS OF THE GRID Parallel

computing

in

the

1980s

focused

researchers’

efforts

on

the

development of algorithms, programs and architectures that supported simultaneity. During the 1980s and 1990s, software for parallel computers focused on providing powerful

mechanisms

for

managing

communication

between

processors,

and

development and execution environments for parallel machines. Successful application paradigms were developed to leverage the immense potential of shared and distributed memory architectures. Initially it was thought that the Grid would be most useful in extending parallel computing paradigms from tightly coupled clusters to geographically distributed systems. However, in practice, the Grid has been utilized more as a platform for the integration of loosely coupled applications – some components of which might be running in parallel on a low-latency parallel machine – and for linking disparate resources (storage, computation, visualization, instruments). Coordination and distribution – two fundamental concepts in Grid Computing. The first modern Grid is generally considered to be the information wide-area year (IWAY). Developing infrastructure and applications for the I-WAY provided a seminar and powerful experience for the first generation of modern Grid researchers and projects. Grid research focuses on addressing the problems of integration and management of software. GRID COMPUTING CHARACTERSTICS An enterprise-computing grid is characterized by three primary features •

Diversity;

•

Decentralization; and

Diversity: A typical computing grid consists of many hundreds of managed resources of various kinds including servers, storage, Database Servers, Application Servers, Enterprise Applications, and system services like Directory Services, Security and Identity Management Services, and others. Managing these resources and their life cycle is a complex challenge.

Decentralization: Traditional distributed systems have typically been managed from a central administration point. A computing grid further compounds these challenges since the resources can be even more decentralized and may be geographically distributed across many different data centers within an enterprise. TYPES OF GRID Grid computing can be used in a variety of ways to address various kinds of application requirements. Often, grids are categorized by the type of solutions that they best address. The three primary types of grids are Computational grid A computational grid is focused on setting aside resources specifically for computing power. In this type of grid, most of the machines are high-performance servers.

Scavenging grid A scavenging grid is most commonly used with large numbers of desktop machines. Machines are scavenged for available CPU cycles and other resources. Owners of the desktop machines are usually given control over when their resources are available to participate in the grid. Data grid A data grid is responsible for housing and providing access to data across multiple organizations. Users are not concerned with where this data is located as long as they have access to the data. For example, you may have two universities doing life science research, each with unique data. A data grid would allow them to share their data, manage the data, and manage security issues such as who has access to what data. THE KIND OF GRID TOOLS Infrastructure components include file systems, schedulers and resource managers, messaging systems, security applications, certificate authorities, and file

transfer mechanisms like Grid FTP. •

Directory services. Systems on a grid must be capable of discovering what services are available to them. In short, Grid systems must be able to define (and monitor) a grid’s topology in order to share and collaborate. Many Grid directory services implementations are based on past successful models, such as LDAP, DNS, network management protocols, and indexing services.

•

Schedulers and load balancers. One of the main benefits of a grid is maximizing efficiency. Schedulers and load balancers provide this function and more. Schedulers ensure that jobs are completed in some order (priority, deadline, urgency, for instance) and load balancers distribute tasks and data management across systems to decrease the chance of bottlenecks.

•

Developer tools. Every arena of computing endeavor requires tools that allow developers to succeed. Tools for grid developers focus on different niches (file transfer, communications, environment control), and range from utilities to fullblown APIs.

•

Security. Security

in a grid environment can mean authentication

and

authorization in other words, controlling who/what can access a grid’s resources -- but it can mean a lot more. For instance, message integrity and message confidentiality are crucial to financial and healthcare environments GRID COMPONENTS:A HIGH LEVEL PERSPECTIVE Depending on the grid design and its expected use, some of these components may or may not be required, and in some cases they may be combined to form a hybrid component. Portal/user interface Just as a consumer sees the power grid as a receptacle in the wall, a grid user should not see all of the complexities of the computing grid. Although the user interface can come in many forms and be application-specific. A grid portal provides the interface for a user to launch applications that will use the resources and services provided by the grid. From this perspective, the user sees the grid as a virtual computing resource just as the consumer of power sees the receptacle as an. interface to a virtual generator.

Figure 2: Possible user view of a grid Security A major requirement for Grid computing is security. At the base of any grid environment, there must be mechanisms to provide security, including authentication, authorization, data encryption, and so on. The Grid Security Infrastructure (GSI) component of the Globus Toolkit provides robust security mechanisms. The GSI includes an OpenSSL implementation. It also provides a single sign-on mechanism, so that once a user is authenticated, a proxy certificate is created and used when performing actions within the grid. When designing your grid environment, you may use the GSI sign-in to grant access to the portal, or you may have your own security for the portal.

Figure 3: Security in a grid environment Broker Once authenticated, the user will be launching an application. Based on the application, and possibly on other parameters provided by the user, the next step is to identify the available and appropriate resources to use within the grid. This task could be carried out by a broker function. Although there is no broker implementation

provided by Globus, there is an LDAP-based information service. This service is called the Grid Information Service (GIS), or more commonly the Monitoring and Discovery Service (MDS). This service provides information about the available resources within the grid and their status. A broker service could be developed that utilizes MDS.

Figure 4: Broker service Scheduler Once the resources have been identified, the next logical step is to schedule the individual jobs to run on them. If sets of stand-alone jobs are to be executed with no interdependencies, then a specialized scheduler may not be required. However, if you want to reserve a specific resource or ensure that different jobs within the application run concurrently then a job scheduler should be used to coordinate the execution of the jobs.. It should also be noted that there could be different levels of schedulers within a grid environment. For instance, a cluster could be represented as a single resource. The cluster may have its own scheduler to help manage the nodes it contains. A higher-level scheduler (sometimes called a meta scheduler) might be used to schedule work to be done on a cluster, while the cluster's scheduler would handle the actual scheduling of work on the cluster's individual nodes.

Figure 5: Scheduler Job and resource management With all the other facilities we have just discussed in place, we now get to the

core set of services that help perform actual work in a grid environment. The Grid Resource Allocation Manager (GRAM) provides the services to actually launch a job on a particular resource, check its status, and retrieve its results when it is complete.

Figure 7: Gram Job flow in a grid environment Enabling an application for a grid environment, it is important to keep in mind these components and how they relate and interact with one another. Depending on your grid implementation and application requirements, there are many ways in which these pieces can be put together to create a solution. ADVANTAGES Grid computing is about getting computers to work together. Almost every organization is sitting on top of enormous, unused computing capacity, widely distributed. Mainframes are idle 40% of the time With Grid computing, businesses can optimize computing and data resources, pool them for large capacity workloads, share them across networks, and enable collaboration. Many consider Grid computing the next logical step in the evolution of the Internet, and maturing standards and a drop in the cost of bandwidth are fueling the momentum we're experiencing today. CHANLLANGES OF GRID A word of caution should be given to the overly enthusiastic. The grid is not a silver bullet that can take any application and run it a 1000 times faster without the need for buying any more machines or software. Not every application is suitable or enabled for running on a grid. Some kinds of applications simply cannot be parallelized. For others, it can take a large amount of work to modify them to achieve faster throughput. The configuration of a grid can greatly affect the performance,

reliability, and security of an organization's computing infrastructure. For all of these reasons, it is important for us to understand how far the grid has evolved today and which features are coming tomorrow or in the distant future CONCLUSION Grid computing introduces a new concept to IT infrastructures because it supports distributed computing over a network of heterogeneous resources and is enabled by open standards. Grid computing works to optimize underutilized resources, decrease capital expenditures, and reduce the total cost of ownership. This solution extends

beyond

data

processing

and

into

information

management

as

well.

Information in this context covers data in databases, files, and storage devices. In this article, we outline potential problems and the means of solving them in a distributed environment. . BIBLIOGRAPHY [1] www.ibm.com/grid/index.html [2] Foster, I. and Kesselman, C. (eds) (1999) The Grid: Blueprint for a New Computing Infrastructure.. San Francisco, CA: Morgan Kaufmann [3] Berman, F., Fox, G. and Hey, T. (2003) Grid Computing: Making the Global Infrastructure a Reality. Chichester: John Wiley & Sons. [4] Web Site associated with book, Grid Computing: Making the Global Infrastructure a Reality, http://www.grid2002.org.

E-Learning: Learning Through Internet (Major area - Web Technologies)

By: S.Sindhuri & K.Preethi CSE, 2nd year. G.Narayannama Institute Of Technology & Science

(For Women) Shaikpet, Hyderabad-500008 Contact: 040-23565648 (exn.313) Phone: 9441606667 E-mail – [email protected]

Abstract:

This paper presents an approach for integrating e-learning with the traditional education system. A conceptual map is then created for this integration leading to a functional model for open and flexible learning. In the proposed integration, convergence of CD-based, class based and web based education in recommended and architecture to achieve this convergence is presented. In order to transform the existing schools, colleges and universities into digital campuses, an inclusive system architecture is designed for digital campus. A case study is given an actual implementation in a conventional school. Integration of e-learning with traditional education is not only possible but also highly effective with the proposed model.

Introduction:

E-learning is part of the Web Technologies. What is e-learning? Advances in Information and Communication Technologies (ICT) have significantly transformed the way we live and work today. This transformation is so ubiquitous and pervasive that we often talk about emergence of “knowledge economy”, “knowledge-based society” and “knowledge ear”. ICT had fundamentally three effects on human society one, the barrier of geography has been dissolved; “Distance is dead” is the new metaphor. Second, the concept time itself has undergone change. Once can interact now synchronously as well as asynchronously. The events can also be simulated and activities can take place in cyber space on pre-defined times scales. Lastly, ICT allows us to individual himself along with the environment in which he is immersed. No wonder, advances in ICT have impacted the human civilization more than anything else in history ever before. E-learning should be defined as learning opportunities delivered and facilitated by electronic means. In this e-learning mode, education contents are delivered by electronic technology. E-learning differs from the traditional system because of the way it is delivered. E-learning imparts all the three main components of learning, namely contents, learning methodologies, and teaching or tutoring methodologies on one hand and e-learning can supplement and complement the traditional system on the other hand. It is the alternative for the traditional education system.

This paper mainly focuses on the difference between traditional education system and e-learning. In e-learning, three different forms of computer based systems have evolved. 1) CD based education (CDE), 2) Class room based learning (CEBE), and 3) Web based learning (WBE) with their own advantages and limitations. Experiments done at ETH Research Lab show that the success of e-learning strategies depends on how best we can combine all the three learning modes. This is the best method for integrating e-learning with the traditional teaching process. The elearning technology can create an open and flexible learning environment with the convergence of CD based, class based and web based education.

Conceptual Model: Traditionally our education system has two distinct processes, namely the learning process and the learning administration or support process. Learning system caters to the development of skills and competencies in the learners through personal learning, group learning group learning in class, learning from teachers and experts, and learning from the experiences of self and others. The e-learning system architecture must address both to the learning process as well as learning support process. In e-learning support processes are equally important as the content and services has to be provided by educational providers (ESPs) as such experts normally dose on the campuses. ETH

Research

Lab

has

advanced

open

and

flexible

e-learning

system

architecture as shown in fig1, providing convergence of formal, non formal and informal education and bringing educational service providers, activity providers, learning resources on one single platform for achieving mass personalized education. The conceptual model has all required subsystems namely learning system, learning support

system,

delivery

system,

maintenance-development-production

system, and total administration and QA system.

(MDP)

Learning system of traditional education system will be enhanced with the availability and accessibility of virtual learning resources.

Fig 1:E-learning conceptual model Learning support system addresses the technology for facilitation of learning system. It will also include the learning from the remote tutors through the virtual class mode, lecture on demand and formative feedback for the assessment and evaluation. Delivery system delivers the content in electronic form to the learners and distributed classrooms. Services management (maintenance, development and production) will help in collaborating with the service providers. This enhances the knowledge repository as compared to the traditional education system. Total management and QA system monitors and manages the quality education delivery to the learners.

Functional model:

The conceptual architecture best describes the convergence of the WBE, CBE, and CEBE. With the field trails and experiments, we have observed that there is a need for the operational support services and mini ERP services for managing the educational institutions. With technology we can make the whole administration and management of education more effective. Our architecture aims at creating a fullfledged digital campus driven by ICT.

Fig – E-learning functional model The conceptual architecture of e-learning described in the previous section can be enhanced with these services for managing the institution.. LMS and LCMS: Functional model for learning system and learning support systems are implemented

as

Learning

Management

System

(LMS)

and

Learning

Content

Management System (LCMS). Content Authoring Tool is useful for creation of the content. With this, teachers can create their own content and publish it. Content creation with the SCORM (Sharable Content Object Reference Model) standards makes

it interchangeable across the LMS. Content Assembly Tools plays an important role in packaging the content prepared with authoring tool and publishing it. Our architecture complies with IMS Content Packaging standards for content assembly tool thus giving interoperability. Learning Objects published with content assembly tools are categorized with the Learning Object Metadata and stored in Catalog Manager.

Fig 3:E-learning LMS system

Course Repository stores the course structures which integrates the learning objects and sequence them. Learning Planner assists learner with the appropriate alternative plans corresponding to the learning objective of the learner. Finally it sends the User Information to the Use Repository. Personalized delivery of the course to the learner is managed with delivery engine in LAN version and WAN version. For the individual leaning and group learning various collaborative services like special interest groups, discussion forum, virtual classroom and various enrichment contents can be delivered through collaboration engine. When we collaborate with the

Educational Service Providers, we need to provide the facility for monitoring and control of the services provided by them. Operational Support Services (OSS) helps in service collaboration, launching, billing, support and maintenance services. ETH Research Lab, we have approached this architecture with the Open Source technologies, independent of platform and databases. Support for multilingual technologies is also provided. XML based integration layer helps in data exchange and collaboration across the systems. Service oriented architecture (SOA): Researchers are implementing the ETH mission in phased manner. They have deployed the computer literacy program in collaboration with university. Now we are extending it through schools and colleges. With digital campus, we will digitize schools and colleges within the campus. Here e-learning will be complementary to the traditional education process. All the digital campuses should collaborate on one platform in order to build the content

and

knowledge

repository

which

can

be

delivered

to

the

students

electronically. This collaborate approach will be driven through the service oriented architecture (SOP). Schematic representation of the SOA implementation is expressed in fig4. Service oriented architecture can be application to the networked digital campus as expressed in the above architecture diagram. We have used J2EE framework to implemented SOA. SOA is a collection of services on a network that communicate with one

another.

The

services

are

loosely

coupled,

have

well-defined,

platform

independent interfaces, and are reusable. SOA is a higher level of application development. Web services use WSDL, UDDI and SOAP. Services provides information. Service providers describe their services in a WSDL document. The URL for WSDL is give in UDDI. With the application of this, the learning system of one campus can be accessed based on the

agreed terms and conditions for service sharing by other campus

through UDDI search. UDDI locates the WDSL file which locates the service on the network. This will deliver the desired learning resources to the learners on single signon.

The common platform is portal which can be used for convergence of educational services from the educational service providers. This service can be easily accessible to various digital campuses as the learning and teaching resources.

Digital School 1 Binds Service Learner

Digital Campus Portal

WSDL

Digital School 2

Digital School “n”

UDDI

Fig 4: Schematic Representation of use of SOA Case Study:

Lectures can be enhanced with the electronic media and can be projected to the student in the classrooms. Interactive CDs help learners to visualize and understand the matter; teachers can make use of computers for making the lectures more lively and effective through multimedia. Documentation management system can help issue and management of bonafied certificates, leaving certificates and other statutory certificates for student and staff. Work flow management system allows management of processes like lecture scheduling; leave management, library management helps in issue and procurement of books. The concept of the Digital School has been implemented where we have digitalized the operations of the schools, CD based content of the school syllabus for teachers and student and web based support and enrichment material. It has got wide

acceptance from the teachers and learners as it reflected the processes and methodologies they have been following in the school. This system now helping in admission process, scheduling of lectures, managing conventional and digital library resources, lecture on demand, students notes, group learning through Special Interest Groups, pre and post examination processes, accounts and finance management, budgetary control, asset management of the school along with the day today administration of attendance payroll and also documentation management of statutory certificates for students. Currently the challenge lies in getting the schools into the e-learning framework, orientation of teachers and making the teachers use the system on their own. Other challenges are installation and maintenance of infrastructure as well as organizing budgets for the digital campus initiative in each institution. With Digital Campus program, schools, colleges, teachers, student, learning resources will be able to collaborate on one platform. The convergence model will have to be supported with quality educational services and activities. Best teachers are made available across the campus and across other institutions through virtual classrooms. Conclusion: After going through the survey work of implementation of e-learning through several schools and colleges with the Open and Flexible Learning Environment architecture, we feel that the success in the co-existence and integration of traditional and e-learning strategies. Current barriers for success of these convergence models are mind set, budgets for infrastructures, preparedness if teachers and local support. However, with marked reduction in the cost of PCs, laptops, networking and servers, introduction of IT subject in school syllabus, spread of affordable internet and growing awareness of the benefits of IT in education, the perceived barriers are getting dissolved. However, there is a great challenge of quality content creation. This must be compliant with the emerging international standards such as SCROM / IMS to be reusable and modifiable. Our objective in this paper was to present an implementable

architecture for integration of e-learning with traditional education in school, colleges and universities. We have also presented the results of our implementations as a case study proving the validity of our architecture and strategies.

References: 1.White paper on “An Implementable Architecture off an e-learning system” by Xiaofel Liu, Abdulmotaleb El Saddik and Nicolas D. Georganas. 2.“e-Learning

Interoperability

Standards”,

Sun

white

paper,

January

2002-

www.sun.com/products-n-solutions/edu/whitepapers/index.html 3.“e-Learning theories and pedagogical Strategies”- hhtp://www.homestead.com 4.“Evaluating the effectiveness of E-Learning Strategies for Small Medium Enterprises” – Eduardo Figueria 5.“ Triple Play Solutions for the Student Residence”- Allied Telesyn

JNTU COLLEGE OF ENGINEERING ANANTAPUR (AUTONOMOUS)

Presented by --K.Siddu Avinash

R.K.Pavan

(05001A0528)

(05001A0513)

ph: 9908966866

ph: 9966537591

Email id: [email protected] [email protected] Abstract

Data warehousing provides architectures and tools for business executives to systematically organize, understand, and use their data to make Strategic decisions. Data Warehouses are arguably among the best resources a modern company owns. As enterprises operate day in day out, the data warehouse may be updated with a myriad of business process and transactional information: orders, invoices, customers, shipments and other data together form the corporate operations archive. As the volume of data in the Warehouse continues to grow so, the time it takes to mine (extract) the required data, individual queries, as well as loading data can consume enormous amounts of processing Power and time, impeding other data warehouse activity; and customers experiences slow response times while the information technology(IT) budget shrinks-this is the data warehouse dilemma Ideal solutions, which perform all the work speedily and with out cost, are obviously impractical to consider. The near-ideal solution would, 1) help reduce load process time, and 2) optimize

available resources for the analysis, to

achieve these two tasks we need to invest in buying additional compute resources. There is a solution, however, enabling the ability to gain compute resources without purchasing additional hardware: Grid computing. Grid Computing provides a novel approach to harnessing distributed resources, including applications, computing platforms or databases and file systems. Applying Grid computing can drive significant benefits to the business by improving information access and responsiveness. The Grid-enabled application layer dispatches jobs in parallel to multiple compute nodes; this parallelization of previously serial tasks to multiple CPU’s is where Grid gets its power. Grids can benefit from sharing existing resources and adding dedicated resources such as clusters to improve throughput. Finally, Grid Computing solution enables the ability to gain compute resources with out purchasing additional hardware.

Basic’s Data warehouse: “A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision making process”. Subject-oriented: A data warehouse is organized around major subjects, such as customer, supplier, product, and sales Integrated: A data warehouse is usually constructed by integrating multiple heterogeneous sources, such as relational databases, flat files, and on-line transaction records. Time-variant:Data

are

stored

to

provide

information

from

a

historical

perspective(e.g., the past 5-10 years) A data warehouse is a copy of transaction data specifically structed for querying, analysis and reporting. Data warehouse is a Star & Snowflake architecture where data is viewed as 3D – cube (multidimensional model).

Grid Technology: Grid technology is a form of distributed computing that involves coordinating and sharing computing, application, data, storage, or network resources across dynamic and geographically dispersed organizations, Grid technologies promise to change the way organizations tackle complex computational problems. With a Grid, networked resources desktops, servers, storage, databases, even scientific instruments can be combined to deploy massive computing power wherever and whenever it is needed most users can find resources quickly, use them efficiently, and scale them seamlessly. There are various types of grids are their viz.. cluster grids, campus grids, global grids e.t.c.

(an eg of global grid)

Introduction A data warehouse is comprised of two processes:loading (input) and analysis (output). Loading a data warehouse is often straightforward. Data is collected from multiple systems of record (extraction), cleansed and normalized to meet the data integrity standards of the warehouse (transformation), and then brought into the warehouse as new records (load): a process referred to as ETL (Extract, Transform and Load). Once the data is loaded, it is ready for analysis. Although analysis can be performed by querying the data warehouse directly, most often smaller data subsets, referred to as data cubes, are created and distributed.

Third-party tools are used to analyze the data within the cubes separately from the warehouse. Depending on the analysis tool,the data cube may need to be built to meet multiple specifications requiring the data to go through a second ETL process. It may be easier to throw more processing power at both processes, but this is not always a cost-effective solution. Although the load process is fundamental to the warehouse, value is derived only

during analysis. Therefore, we can target the non-value-added load step and seek to reduce its impact on warehouse resources. The near-ideal solution : Ideal solutions, which perform all the work speedily and without cost, are obviously impractical to consider. The near-ideal solution would, 1) help reduce load process time, and 2) optimize available resources for the analysis process at a cost lower than upgrading hardware. Focusing on reducing the load process first, the computing burden is primarily the result of the transformation step (cleansing and normalization). The addition of compute resources can accelerate the transformation step; however, it must be more cost-effective than upgrading hardware. During transformation, a given set of rules is applied to a set of data. Often the data is discrete, not dependent on relationships to external data (e.g., when processing market data, each market territory is typically treated with the same rules but processed independently). Without dependencies between units of work, changing the serial model to a parallel model can accelerate processing. Processing multiple work units at once reduces the time required by the transformation step and thereby meets the first criteria to help reduce the load process. Moving to a parallel model requires the addition of compute resources, which would correspondingly satisfy the second criteria of optimizing resource availability for analysis—although the cost of adding compute resources must be lower than upgrading the data warehouse hardware. There is a solution, however, enabling the ability to gain compute resources without purchasing additional hardware: Grid computing. Off-loading ETL process to a Grid environment can lower the processing cost, reduce the cycle time, and enable the reallocation of critical data warehouse resources for use by data mining and reporting tools. Providers may eventually use information Grids to enable their customers to access the data in a virtual data warehouse environment as if it was stored locally. Harnessing distributed resources with Grid computing: Grid computing enables the virtualization of distributed computing

over a network of heterogeneous resources—such as processing, network bandwidth and storage capacity—giving users and applications seamless, on demand access to vast IT capabilities. Using power of open standards, it enables computing capacity to be dynamically procured and released based on variations in peak loads - offering business value in day-to-day operations as well as great response and recovery. Grid computing provides a novel approach to harnessing distributed resources , including applications, computing platforms or databases and file systems. Applying Grid computing can drive significant benefits to the business by improving information access and responsiveness, and adding flexibility, all crucial components of solving the data warehouse dilemma. By placing CPUs into a virtual resource pool, more power can be applied where needed. Achange at the application layer is required to take advantage of the new architecture: a task often performed in days. The Grid-enabled application layer dispatches jobs in parallel to multiple compute nodes; this parallelization of previously serial tasks to multiple CPUs is where Grid gets its Power. The ability to execute transformation tasks independently enables the load process to be broken into multiple subprocesses, which can be sent to a different node in the virtual pool. ( for eg, to find no of people who have age > 18 in A.P (suppose A.P census data is maintained in an data warehouse) approximately 7 crore of data need to processed by a single CPU (server), assuming data is denormalised) it may take some hours. if A.P census dept has 28 computers ( this can be combined to form a grid) then we can distribute 25 lakhs of data to each CPU , then the results may be achieved with in minutes) similarly, in medical system to obtain the details of patient’s who used a specific drug.

(using sun cluster grid The Durham university cosmology Engine Performs 465 billon arithmetic operations per second on a sun cluster grid) ( sun as a grid of over 7,500 total CPU’s across 3 us sites, with over 98 % CPU utilization excuting over 50,000 EDA job’s a day) further, to guard against downtime and failures, each subprocess can be sent to multiple nodes—each competing to return the results first, eliminating the single point of failure while guaranteeing the fastest response time. The nodes that form the virtual pool may already exist as underutilized servers within the organization. Grids can benefit from not only sharing existing resources, but also from adding dedicated resources such as clusters to improve throughput. This would help improve predictability in completion of a job governed by service level agreements (SLAs). By adding new hardware to the Grid, resource utilization can be optimized versus dedicating the hardware to one particular process. Best of all, “Grid is a mature technology that has already been scrutinized and proven successfully”.

New technology security concerns: As expected, Grid computing addresses universal concerns regarding new technology, including security, scalability and reliability. Security is managed at multiple levels: •At the user level, the Grid middleware server performs rights management, abstracting the user from the Grid resources. •At the data level, data is encrypted during transmission between Grid nodes and the Grid middleware server. •At the process level, the Grid middleware operates in a virtually tamperproof“sandbox” to help prevent viewing or modifying the data or process. Scalability is one of the inherent capabilities of Grid computing. As a virtual pool of resources, scalability is governed by the limitations of the size of data being transferred and available bandwidth. There aren’t any inherent restrictions on the size of a Grid, and reliability is addressed through multiple approaches. Tasks can be constructed so a node failure prompts the Grid mid-dleware to resubmit the job to another node. Alternately, jobs can be submitted to multiple nodes and accept the first response, thus helping to eliminate the concern of a single point of failure while providing the fastest response time. Building on the concept of virtualizing computing power into resource pools,information Grids treat data silos as information pools with nearby storage pools. Data required by the warehouse can be accessed via the information Grid where domain security management is handled automatically. Data transformations can be performed at the remote client and the results brought back across the network, encrypted for privacy. Retrieved data is cached to improve performance with mechanisms for expira-tion to verify that only the most recent data is available. The resulting solution is not a replacement for guaranteed delivery-messaging solutions. However,for less time dependent business intelligence, the solution is designed to provide the needed functionality at the lowest possible cost by leveraging the existing infrastructure. As an added benefit, the information Grid provides a new IT service, enabling remote silos to access each other. This opens up an entirely new realm of time-independent opportunities such as data replication and inherent resiliency.

Making it happen: To determine if your data warehouse can benefit from Grid technologies, it’s necessary to institute a process of investigation. A good place to start is by inventorying all the ETL processes and evaluating the big hitters. Another good, low-risk place to start is by engaging a consultant with Grid experience.

Conclusion : Grid computing introduces a new concept to IT infrastructures because it supports distributed computing over a network of heterogeneous resources and is enabled by open standards. Grid computing—which helps optimize underutlized resources, decrease expenses and reduce costs—has helped organizations accelerate business processes, enable more innovative applications, enhance productivity, and improve resiliency of IT infrastructure. finally, applying grid technology to a data warehouse can reduce the cost , with out purchasing the additional hardware.

References : Modern data ware housing, mining & Visualization Building the data ware house sun.com/software/grid/ gridcomputing.com gridpartner.com ibm.grid/

- marakas - immon

Network security and protocols VULNERABILITY IN TCP/IP

PRESENTED BY: G.Ramya Krishna.

B. Durga Raja Sena.

II/IV –B-Tech,CSE

II/IV –B-Tech,CSE

ID: 06091A0573

ID: 06091A0524

[email protected]

[email protected]

RAJEEV GANDHI MEMORIAL COLLEGE OF ENGINEERING AND TECHNOLOGY.

Affiliated to J.N.T.U, HYDERRABAD. Accredited by NBA, NEW DELHI.

Abstract: Network security is a complicated subject, historically only tackled by well trained and

experienced experts. However as more and more people become

"wired" an increasing number of people need to understand the basics of security in a networked world in this document we discuss some of the network security issues in TCP/IP. The Transmission control protocol/Internet protocol (TCP/IP) suite is a very widely used

technique that is employed inter connect computing facilities in

modern network environments TCP/IP is the "language" of the internet. Anything that can learn to "Speak TCP/IP" can play on the internet. However , there exist several security vulnerabilities in the TCP specification and additional

weaknesses in a number of widely available implementations of TCP.

These vulnerabilities may

unable an intruder to "attack" TCP - based systems,

enabling him or her to "hijack" a TCP connection

are cause denial of service to

legitimate users. We discuss some of the flaws present in the TCP implementation of many widely used operating system and provide recommendations to improve the security state of a TCP-based system. e.g., incorporation of a "Timer escape route" from every TCP state.

Keywords and phrases: Network security, TCP, IP, Vulnerability analysis, state transitions

INTRODUCTION: Internet working is an approach that allows dissimilar computers on dissimilar networks to

communicate with one another in seamless fashions by hiding the

details of the underlying network hardware. The most widely used form of internet working is provided by the transmission control protocol/Internet protocol (TCP/IP) suite. There are some inherent security problems in the TCP/IP suite which makes the

situation conducive to intruders. TCP sequence numbers prediction, IP

address spoofing, misuse of IP's

source routing principle, use of internet control

message protocol (ICMP) messages denial of service, etc are some methods to exploit the networks vulnerabilities. Considering the fact that most important programs

such

as

simple

mail

transfer

application

protocol(SMPP),Telnet-

commands(rlogin,rsh,etc),file transfer protocol(FTP),etc. have TCP as their transport layer, security flaws in TCP can prove to be very hazardous for the network. The objectives of this paper are to identify and analyze the vulnerabilities of TCP/IP and to develop security enhancements to overcome those flaws. Our work is based on analyzing the state transition diagram of TCP and determining the security relevance of some of the “improperly-defined” transitions between different states in the state transition diagram of many widely used TCP code implementations.

TCP/IP The TCP Protocol uses a simple method to establish communications between computers. The origination computer (the one trying to start a communications “session”) sends an initial bit of data or packet called a “SYN” to the computer or other device with which it needs to communicate. The “target” computer answers the original computer with another data packet called an “ACK” or acknowledgement. The original computer then returns an “ACK” packet back to the “target” computer.

This process is referred to as the SYN-ACK “handshake” or the “three-way handshake” and is characteristic of all TCP/IP communications. This process is illustrated in Figure B.6-1.

NETWORK ` Workstation Send Request Read

Server Accept

ACK ta + e Da s n o sp + Re SYN TCP

TIME

TCP SYN + Re spon se D ata

TIME

Wakeup Close

Web Server

Wakeup Process Request / Send Response

ACK

Figure B.6-. TCP-IP “Handshake”

Security Issues SYN Flood Attack TCP/IP uses a “best effort” method in delivering packets, which just means that it has no real way to guarantee the delivery of a packet to its destination. It’s interesting to consider that the Post Office uses this method as well. One of the consequences of this is that message latency and packet loss are not uncommon which can result in messages arriving late or in non-sequential order. The TCP part of TCP/IP uses sequence numbers to identify packets and to help ensure that it is given to the user in the correct order regardless of when the data is

actually received. These sequence numbers are initially established during the opening phase of a TCP connection, in the three-way handshake illustrated in Figure B.6-1. One way that “hackers” exploit TCP/IP is to launch what is called a SYN attack (sometimes called “SYN Flooding”) which takes advantage of how hosts implement the “three-way handshake.” When the “target” computer (illustrated in B.6-1) receives a SYN request from the originating computer, it must keep track of the partially opened connection in what is called a "listen queue" for at least 75 seconds. This was built into TCP/IP to allow successful connections even with long network delays.

The problem with doing this is that sometimes the TCP/IP is configured so that it can only keep track of a limited number of connections (most do 5 connections by default, although some can track up to 1024). A person with malicious intent can exploit the small size of the listen queue by sending multiple SYN requests to a computer or host, but never replying to the SYN-ACK the “target” sends back. By doing this, the host's listen queue is quickly filled up, and it will stop accepting new connections, until a partially opened connection in the queue is completed or times out.

The classic SYN flood was introduced in 1993 by members of the CompuServe “Internet chat” community as a method of removing “undesirables” from chat rooms or networks. The first UNIX programs to utilize this method were synflood.c (circa 1993) and nuke.c Satanic Mechanic (circa 1992/1993). This ability to effectively remove a host from the network for at least 75 seconds can be used solely as a denial-of-service attack, or it can be used as a tool to implement other attacks, like IP Spoofing.

Vulnerabilities IP Spoofing The Internet Protocol (IP) portion of TCP/IP is the part that carries the information describing where the packet is coming from and where it’s going to. This information is called the “IP Address.” “IP Spoofing” is an attack where an attacker pretends to be sending data from an IP address other than his own. TCP/IP assumes that the source address on any IP packet it receives is the same IP address as the system that actually sent the packet (which is a vulnerability of TCP/IP in that it incorporates no authentication.) Many higher level protocols and applications also make this assumption, so anyone able to fake (or “forge”) the source address of an IP packet (called "spoofing" an address) could get authorized privileges as an unauthorized user. There are two disadvantages to this spoofing technique. The first is that all communication is likely to be one-way. The remote host will send all replies to the spoofed source address, not to the host actually doing the spoofing. So, an attacker using IP spoofing is unlikely to see output from the remote system unless he has some other method of eavesdropping on the network between the other two hosts. Additional information is available in the IT white paper, Intrusion Prevention & Detection. The second disadvantage is that an attacker needs to use the correct sequence numbers if he plans on establishing a TCP connection with the compromised host. Many “common” applications or services that run on many operating systems, like Telnet and FTP, use TCP. The final ACK in the three-way handshake must contain the other host's first sequence number, known as the initial sequence number or ISN. If TCP/IP does not “see” this ISN in the ACK, the connection cannot be completed because the ISN in the SYN+ACK packet is sent to the real host, an attacker must “steal” this ISN by some technical method. If he could “eavesdrop” on the packets sent from the other host (using an IDS or protocol analyzer), he could see the ISN. Unfortunately, attackers have developed new ways to overcome both of these challenges to IP Spoofing.

Source Routing Another way to do IP spoofing makes use of an IP option which is rarely used called "source routing." Source routing allows the originating host to specify the path (route) that the receiver should use to reply to it. Any attacker can take advantage of this by specifying a route that by-passes the real host, and instead directs replies to a path it can monitor (probably to itself). Although simple, this attack may not be as successful now, as most routers are commonly configured to drop packets with source routing enabled.

Connection or “Session” Hijacking Yet another way to accomplish IP spoofing is for a host to insert itself in the middle of a connection between two hosts. This is called “connection hijacking” or “session hijacking.”

IP spoofing alone may not bypass additional security,

such as an authentication measure that we have added or enforced on our operating system,

but with this attack,

an attacker can allow normal

authentication to proceed between the two hosts, and then seize control of the connection. Session hijacking exploits a "desynchronized state" in TCP communication. This happens when the sequence number in a received packet is not the same as the expected sequence number. In this case, the connection is said to be "desynchronized." Depending on the actual numerical value of the received sequence number, TCP may either discard or store the packet in its queue. TCP has a choice, because it uses a “sliding window” application or protocol for efficient communication even if the network has extensive packet loss.

If the

received packet is not the one TCP expected, but is within the current “window,” the packet will be saved and TCP will expect it later.

If the received packet is

outside of the current window, it is discarded. The result is that when two hosts are desynchronized enough they will discard (or ignore) packets from each other. The attacker can then inject ‘forged’ packets with the correct sequence numbers (and potentially modify or add commands to the packet).

This exploit is usually perpetrated by an “insider” because it requires the attacker to be located in the communication path between the two hosts to “listen-in and replicate packets being sent. The key to this attack is creating the desynchronized state. Note that "ignored" or discarded packets may actually generate ACKs, rather than being completely ignored. When the other end receives packets with wrong sequence numbers, it sends back an ACK packet with the sequence number it is expecting. The receiver of these ACK discards them, since they have the wrong sequence numbers. The receiver then sends its own ACK to notify the sender. In this way, a large number of ACKs are generated forming the attack. This is a classic "signature" employed by Intrusion Detection Systems (IDS) to detect session hijacking. Additional information on intrusion detection is available in the IT white paper,

Intrusion Prevention & Detection.

ICMP Attack The Internet control message protocol (ICMP) is used in networking to send a one-way informational message to a host or device. The most common use of ICMP is the "PING" utility. This application sends an ICMP "echo request" to a host, and waits for that host to send back an ICMP "echo reply" message. This utility application is very small and has no method of authentication and is consequently used as a tool by “an attacker to intercept packets or cause a denial of service. Attackers almost always use either the "time exceeded" or "destination unreachable" messages that can be generated by ICMP to carry out the attack. The "time exceeded" message describes the “time-to-live” or the amount of time allocated for a packet to exist as it travels around the network. This can normally be caused by trying to reach a host that is extremely distant. "Destination unreachable" basically indicates that packets cannot successfully be sent to the desired host. Both of these ICMP messages can cause a host to

immediately drop a connection (which is what you want if the ICMP message is legitimate). An attacker can make use of this by forging one of these ICMP messages, and sending it to one or both of the communicating hosts which breaks their connection. These are just some of the more common attacks that can occur because of the nature and design of the TCP/IP protocol. As we mentioned earlier, we must employ additional technology and practices to compensate for this shortfall in TCP/IP. These measures are characterized as Internet security.

Internet Security Measures Firewalls The most common technology applied to Internet Security today is the firewall. The first firewalls were originally “packet filters.” Since this filtering can be accomplished on dedicated computers placed in the network or on the router at the boundary of the network these “first generation” firewalls are often referred to as screening routers. Packet filtering uses access control lists or “rules” which tell the firewall what to let into the network and what to reject. These rules are sequentially applied to each packet that is received.

The packet filter firewall

also examines each incoming packet’s source and destination IP address to be sure that it is directed to a legitimate or “real” computer and that the sender is not on the inside of our network. That is a symptom of a potential compromise since packets destined for a computer on the safe side of the firewall wouldn’t need to go through it to the unsafe side and back again. An example of a packet filter firewall is the PIX firewall from Cisco. Firewalls are extremely effective in preventing IP spoofing attacks. This is primarily due to their packet filtering abilities. The most effective ability firewalls have in terms of preventing spoofing attacks is that they clearly define the outside or “untrusted” side of the firewall from the inside or “trusted” side of the firewall. They force everything inside to go through the ”inside” interface or port on the firewall, and everything outside must come in through the “outside” interface. This means that the packet filtering done in the firewall can drop

suspicious packets. If the firewall detects a packet coming from the outside that has a source inside the firewall it is probably a spoofed packet, and should be dropped. That’s suspicious because a packet originating inside our network could be destined for an address outside but would NOT be trying to get back through to the inside from the outside of our firewall. Likewise, if a packet attempts to exit the firewall with an address from anywhere other than inside our firewall it can be dropped immediately because it is almost surely “spoofed.” Packet filtering also segments the Internet into smaller zones, which then can not spoof each other. However, even with a firewall, all spoofing within our network cannot be prevented.

Figure B.6-2 illustrates a typical Internet firewall configuration. In this example, the wide area network router is directly connected to the Internet provider and the “outside” or Internet facing port of the firewall is directly connected to this router. The “inside” interface of the firewall is connected to a network switch that in turn serves as the distribution point for the rest of the network.

Internet-Facing Router

Internet

Boundary Firewall

Network Switch

Network Intrusion Detection

Applications

•

Spyware -

Database

E-Mail

is a computer program which can be installed on personal

computers (usually without the permission from the owner) and has as its sole purpose, the collecting of personal information and sending it back to another source - usually an Internet marketing firm but possibly a hacker. A similar type of application is known as “Adware” which behaves in a similar manner but almost always asks permission to be installed beforehand.

U t h se ce e a r’s C rti uth bro e r fic e w t if at n se i c e ti c r a t a it v e ga y o e r S i n f i fi er s th e s ve t t e r he

We can have the certificate server check the user’s identity against our directory server to be sure she’s supposed to have access to the information accessible through the Web site.

Certificate Server (Authentication )

Directory Server (User Identity )

Internet

Browser now maintains an authenticated , encrypted path from the laptop to the Web site .

Authorized user accesses a “secure” Web site and the server “downloads” certificate to the user’s browser .

Authorized User Web Server (Running SSL Protocol )

figure: ssl process Client-based remote access is the other method for providing secure, remote access. In this case, we do not rely on the web browser on our laptop or remote access computer, as we described in the SSL section, but on another piece of software typically referred to as the client or VPN client. VPN, as we noted earlier stands for virtual private network. Additional information on VPNs is available in the IT white paper, Boundary Security.

As we have discussed in Ohio IT Policy ITP-B.2, “Boundary Security,” a VPN is “a private communications network used by many organizations and agencies to communicate confidentially over a public networked environment.”

This can be

thought of as a “tunnel” that allows our traffic to travel through public networks without exposing our agency’s IP packet information to the outside world. Typically, VPN’s will use encryption to provide confidentiality, sender authentication and message integrity to achieve the necessary privacy. For remote access configurations, remote access client software is installed on the

remote computing device and this software will create the VPN “tunnel” from the remote computing device through the firewall to the VPN hardware providing the secure connection. This process is illustrated in figure B.6-5. Note that before the VPN establishes the secure “session” or transmission, proper authentication must take place. If we have determined that our remote access requires the security of a VPN, then we will usually require at least two forms of authentication. This is known as “two-factor” authentication and provides a higher level of security than a user name and password. Additional information on two-factor authentication is available in the IT white paper, Password and PIN Security.

Conclusion The main objective of this was to identify and analyze some new vulnerabilities of TCP/IP. We have discussed different attacks that can be launched by an intruder who manipulates

the

security

implementations. We have

flaws in

the

TCP/IP

specification

analyzed the TCP source code

as well as

its

and identified spurious

state-transitions present in the implementation of TCP in several operating systems. We have analyzed how TCP behaves for various combination of input packets. Finally, we provide several recommendations to

plug some of these flaws in TCP and its

implementations.

References: J.Postel, Transmission Control Protocol. IP Spoofing Attacks and Hijacked Terminal Connections Journal Computer Networks by Tenenbaum