Bio Metrics
This document was uploaded by user and they confirmed that they have the permission to share it. If you are author or own the copyright of this book, please report to us by using this DMCA report form. Report DMCA
Overview
Download & View Bio Metrics as PDF for free.
More details
- Words: 1,270
- Pages: 44
Biometrics and Privacy
What is Biometrics ? Biometrics are automated methods of recognizing a person based on a physiological or behavioral characteristic. Identification and personal certification solutions for highly secure applications.
Why the Interest in Biometrics? Authentication mechanisms often used are User ID and Passwords. Need not have multiple passwords or difficult passwords. Need not remember passwords. Need not carry any cards or tokens. Can’t be separated. Biometrics systems are more convenient. Perceived as more secure
Three-steps Ca pt ur e-Proce ss-V erif ica ti on Ca pt ur e: A raw biometric is captured by a sensing device such as fingerprint scanner or video camera Proce ss: The distinguishing characteristics are extracted from the raw biometrics sample and converted into a processed biometric identifier record
Called biometric sample or template
Verifi ca ti on and Id ent if ication
Verification Compare a sample against a single stored template.
?
Verification (1:1 match) Person Scan
Image Encode
YES
Template 0110100100010010
Match?
NO
0110100100010010 01101 01000
Are you who you
10010
ID token
claim you are ?
Identification Search a sample against a database of templates.
?
Identification (1:N search) Person
Image
Scan
Encode
YES (found)
Template 0110100100010010
Match?
NO (not found)
0110100100010010
Who are you? Are you in our database?
0110100100010010 0101011000110010
Database
Biometrics Today Fingerprints Retina Prints Face Prints DNA Identification Voice Prints Palm Prints Handwriting Analysis Etc…
Accuracy Rates: False Acceptance Rate (FAR)
Measures the percent of invalid users who are incorrectly accepted as genuine users.
False Rejection Rate (FRR)
Measures the percent of valid users who are rejected as impostors.
Equal Error Rate (EER)
Rate at which FAR and FRR match.
Accuracy Rates (contd.) The lower the EER, the more accurate the system is considered to be.
Issues and Concerns
Ph ys ical - Some believe this technology can cause physical harm to an individual using the methods, or that instruments used are unsanitary. Pe rs onal In format ion - There are concerns whether our personal information taken through biometric methods can be misused, tampered with, or sold. Voters may be scared off if forced to give a fingerprint.
Uses and initiatives Brazi l
Brazilian government has decided to adopt fingerprint-based Id cards.
United St at es
The US Department of Defense (DoD) Common Access Card, is a fingerprint-based ID card issued to all US Service personnel and contractors on US Military sites.
Uses and Initiative (contd..) Germany
In May 2005 the German Upper House of Parliament approved the implementation of the ePass, a passport issued to all German citizens which contain biometric technology.
Aust ra li a
Visitors intending to visit Australia may soon have to submit to biometric authentication.
Biometrics in Detail
Biometrics Today Fingerprints Retina Prints Face Prints DNA Identification Voice Prints Palm Prints Handwriting Analysis Etc…
FI NGE RPRINTS
Introduction What makes a fingerprint so special? A fingerprint is unique No two fingerprints from different fingers have been found to have the same ridge pattern. A fingerprint doesn’t change, A fingerprint ridge patterns are unchanging throughout life.
Fingerprint (contd..) Ridge ending
Ridge bifurcation
Finger-scan A live acquisition of a person’s fingerprint. Ima ge Acqu isi tio n → Ima ge Pro cessi ng → Te mpl at e Cre at ion → Templa te Mat ching
Image Capture Optical fingerprint
- Finger on a glass surface - A Laser Light - CCD array captures the reflected light.
Fi nger pr in t P atte rn Ty pe s Loo p Wh orl Ar ch
Finge rprint Pa ttern Types (contd. )
Loo p In a loop pattern, the ridges enter from either side, re-curve and pass out or tend to pass out the same side they entered.
Finge rprint Pa ttern Types (contd. )
Whorl In a whorl pattern, the ridges are usually circular.
Finge rprint Pa ttern Types (contd. )
Arc h In an arch pattern the ridges enter from one side, make a rise in the center and exit generally on the opposite side.
Fingerprint ma tch ing a pproach es Mi nut iae B ased This approach analyses ridge bifurcations and endings. Cor rec tion Bas ed This approach considers the flow of ridges in terms of, for example, arches, loops and whorls.
Chara cteris tic s of two m ajo r a ppr oa ches :
Image Processing and Verification Stages Capture fingerprint Image
•Hardware •Image specification •Noise (Image Enhancement)
Feature Extraction •Minutia approach Verification
Image Proces. & Verif. (Ima ge Enha nce ment )
Original image with noise. Source of noise, the finger tip itself become dirty, cut, scarred, creased, dry, wet, worn etc.
Image Proces. & Verif. (Ima ge Enha nce ment )
• •
Image Enhancement step Reduce noise Enhance ridges and valleys Based on the redundancy of parallel ridges.
Image Proces. & Verif. (Ima ge Enha nce ment )
Matched filters Applied on very pixel, based on the local orientation around each pixel. Enhance ridges oriented in same direction. Decrease anything that orienting differently.
Image Proces. & Verif. (Ima ge Enha nce ment )
Simplifying the color depth from the original 8-bit color depth to 1bit pixel color. Ridge against background
Image Proces. & Verif. (Ima ge Enha nce ment )
Thinning Reduce the width of a ridges down to a single pixel.
Image Proces. & Verif. (Fea tu re Ex tra cti ng )
Find minutiae Remove those attributes that are created by noise, based on the previous images.
Image Proces. & Verif. (Fea tu re Ex tra cti ng )
Result is a minutia template 400 bytes to store a fingerprint.
Image Proces. & Verif. (Verif ic at io n )
Distance functions between the attributes. Threshold.
Fingerprint Str eng ths :
Fingerprints don’t change over time Widely believed fingerprints are unique
We akn esse s:
Scars
At tacks :
Surgery to alter or remove prints “Gummy fingers” Corruption of the database
Def ense s:
Measure physical properties of a live finger (pulse)
Facial Scan Based on video Images Templates can be based on previously-recorded images. Technologies:
Eigen-face Approach. Feature Analysis (Visionics). Neural Network.
Iris Scan Image Acquisition → Image Processing → Template Creation → Template Matching Uses: Physical access control Computer authentication
Iris Scan (contd.): Str eng ths :
300+ characteristics; 200 required for match
We akn esse s:
Fear Discomfort
At tacks :
Surgery (Minority Report )
Voice Strengths:
Most systems have audio hardware Works over the telephone Can be done covertly Lack of negative perception
Weaknesses:
Background noise (airplanes) No large database of voice samples
Attacks:
Tape recordings Identical twins / sound alikes
Defenses:
Hand Scan Typ ical systems meas ur e 90 dif ferent featur es:
Overall hand and finger width Distance between joints Bone structure
Pri ma ril y for acces s control :
Machine rooms Olympics
Streng th s:
No negative connotations – nonintrusive Reasonably robust systems
Wea knes ses :
Accuracy is limited; can only be used for 1-to-1 verification Bulky scanner
Oddballs Retina Scan
Very popular in the 1980s military; not used much anymore.
Facial Thermo grams Vein identification Scent Detection Gait recognition
Biometric Template Size Biometr ic Voice
App rox Templa te Si ze 70k – 80k
Face
84 bytes – 2k
Signature
500 bytes – 1000 bytes
Fingerprint
256 bytes – 1.2k
Hand Geometry
9 bytes
Iris
256 bytes – 512 bytes
Retina
96 bytes
What is Biometrics ? Biometrics are automated methods of recognizing a person based on a physiological or behavioral characteristic. Identification and personal certification solutions for highly secure applications.
Why the Interest in Biometrics? Authentication mechanisms often used are User ID and Passwords. Need not have multiple passwords or difficult passwords. Need not remember passwords. Need not carry any cards or tokens. Can’t be separated. Biometrics systems are more convenient. Perceived as more secure
Three-steps Ca pt ur e-Proce ss-V erif ica ti on Ca pt ur e: A raw biometric is captured by a sensing device such as fingerprint scanner or video camera Proce ss: The distinguishing characteristics are extracted from the raw biometrics sample and converted into a processed biometric identifier record
Called biometric sample or template
Verifi ca ti on and Id ent if ication
Verification Compare a sample against a single stored template.
?
Verification (1:1 match) Person Scan
Image Encode
YES
Template 0110100100010010
Match?
NO
0110100100010010 01101 01000
Are you who you
10010
ID token
claim you are ?
Identification Search a sample against a database of templates.
?
Identification (1:N search) Person
Image
Scan
Encode
YES (found)
Template 0110100100010010
Match?
NO (not found)
0110100100010010
Who are you? Are you in our database?
0110100100010010 0101011000110010
Database
Biometrics Today Fingerprints Retina Prints Face Prints DNA Identification Voice Prints Palm Prints Handwriting Analysis Etc…
Accuracy Rates: False Acceptance Rate (FAR)
Measures the percent of invalid users who are incorrectly accepted as genuine users.
False Rejection Rate (FRR)
Measures the percent of valid users who are rejected as impostors.
Equal Error Rate (EER)
Rate at which FAR and FRR match.
Accuracy Rates (contd.) The lower the EER, the more accurate the system is considered to be.
Issues and Concerns
Ph ys ical - Some believe this technology can cause physical harm to an individual using the methods, or that instruments used are unsanitary. Pe rs onal In format ion - There are concerns whether our personal information taken through biometric methods can be misused, tampered with, or sold. Voters may be scared off if forced to give a fingerprint.
Uses and initiatives Brazi l
Brazilian government has decided to adopt fingerprint-based Id cards.
United St at es
The US Department of Defense (DoD) Common Access Card, is a fingerprint-based ID card issued to all US Service personnel and contractors on US Military sites.
Uses and Initiative (contd..) Germany
In May 2005 the German Upper House of Parliament approved the implementation of the ePass, a passport issued to all German citizens which contain biometric technology.
Aust ra li a
Visitors intending to visit Australia may soon have to submit to biometric authentication.
Biometrics in Detail
Biometrics Today Fingerprints Retina Prints Face Prints DNA Identification Voice Prints Palm Prints Handwriting Analysis Etc…
FI NGE RPRINTS
Introduction What makes a fingerprint so special? A fingerprint is unique No two fingerprints from different fingers have been found to have the same ridge pattern. A fingerprint doesn’t change, A fingerprint ridge patterns are unchanging throughout life.
Fingerprint (contd..) Ridge ending
Ridge bifurcation
Finger-scan A live acquisition of a person’s fingerprint. Ima ge Acqu isi tio n → Ima ge Pro cessi ng → Te mpl at e Cre at ion → Templa te Mat ching
Image Capture Optical fingerprint
- Finger on a glass surface - A Laser Light - CCD array captures the reflected light.
Fi nger pr in t P atte rn Ty pe s Loo p Wh orl Ar ch
Finge rprint Pa ttern Types (contd. )
Loo p In a loop pattern, the ridges enter from either side, re-curve and pass out or tend to pass out the same side they entered.
Finge rprint Pa ttern Types (contd. )
Whorl In a whorl pattern, the ridges are usually circular.
Finge rprint Pa ttern Types (contd. )
Arc h In an arch pattern the ridges enter from one side, make a rise in the center and exit generally on the opposite side.
Fingerprint ma tch ing a pproach es Mi nut iae B ased This approach analyses ridge bifurcations and endings. Cor rec tion Bas ed This approach considers the flow of ridges in terms of, for example, arches, loops and whorls.
Chara cteris tic s of two m ajo r a ppr oa ches :
Image Processing and Verification Stages Capture fingerprint Image
•Hardware •Image specification •Noise (Image Enhancement)
Feature Extraction •Minutia approach Verification
Image Proces. & Verif. (Ima ge Enha nce ment )
Original image with noise. Source of noise, the finger tip itself become dirty, cut, scarred, creased, dry, wet, worn etc.
Image Proces. & Verif. (Ima ge Enha nce ment )
• •
Image Enhancement step Reduce noise Enhance ridges and valleys Based on the redundancy of parallel ridges.
Image Proces. & Verif. (Ima ge Enha nce ment )
Matched filters Applied on very pixel, based on the local orientation around each pixel. Enhance ridges oriented in same direction. Decrease anything that orienting differently.
Image Proces. & Verif. (Ima ge Enha nce ment )
Simplifying the color depth from the original 8-bit color depth to 1bit pixel color. Ridge against background
Image Proces. & Verif. (Ima ge Enha nce ment )
Thinning Reduce the width of a ridges down to a single pixel.
Image Proces. & Verif. (Fea tu re Ex tra cti ng )
Find minutiae Remove those attributes that are created by noise, based on the previous images.
Image Proces. & Verif. (Fea tu re Ex tra cti ng )
Result is a minutia template 400 bytes to store a fingerprint.
Image Proces. & Verif. (Verif ic at io n )
Distance functions between the attributes. Threshold.
Fingerprint Str eng ths :
Fingerprints don’t change over time Widely believed fingerprints are unique
We akn esse s:
Scars
At tacks :
Surgery to alter or remove prints “Gummy fingers” Corruption of the database
Def ense s:
Measure physical properties of a live finger (pulse)
Facial Scan Based on video Images Templates can be based on previously-recorded images. Technologies:
Eigen-face Approach. Feature Analysis (Visionics). Neural Network.
Iris Scan Image Acquisition → Image Processing → Template Creation → Template Matching Uses: Physical access control Computer authentication
Iris Scan (contd.): Str eng ths :
300+ characteristics; 200 required for match
We akn esse s:
Fear Discomfort
At tacks :
Surgery (Minority Report )
Voice Strengths:
Most systems have audio hardware Works over the telephone Can be done covertly Lack of negative perception
Weaknesses:
Background noise (airplanes) No large database of voice samples
Attacks:
Tape recordings Identical twins / sound alikes
Defenses:
Hand Scan Typ ical systems meas ur e 90 dif ferent featur es:
Overall hand and finger width Distance between joints Bone structure
Pri ma ril y for acces s control :
Machine rooms Olympics
Streng th s:
No negative connotations – nonintrusive Reasonably robust systems
Wea knes ses :
Accuracy is limited; can only be used for 1-to-1 verification Bulky scanner
Oddballs Retina Scan
Very popular in the 1980s military; not used much anymore.
Facial Thermo grams Vein identification Scent Detection Gait recognition
Biometric Template Size Biometr ic Voice
App rox Templa te Si ze 70k – 80k
Face
84 bytes – 2k
Signature
500 bytes – 1000 bytes
Fingerprint
256 bytes – 1.2k
Hand Geometry
9 bytes
Iris
256 bytes – 512 bytes
Retina
96 bytes
Related Documents
Bio Metrics
October 2019 25
Bio Metrics
June 2020 15
Bio Metrics
November 2019 19
Bio-metrics
June 2020 11
Bio Metrics
June 2020 11
Bio Metrics 1
June 2020 3More Documents from ""
Gsm Sim & Security
June 2020 11
What Is Wimax?
June 2020 8
Gsm Services
June 2020 5
