Biometrics Tasanawan Soonklang. 2 Biometrics Biometrics – what is? Applications – who use?...

BiometricsTasanawan Soonklang

2

Bio

metrics

• Biometrics – what is?

• Applications – who use?

• Operation – how does it work?

• Types – what are the different?

• Issues – how to choose? , accuracy, concerns

• IT r elated to biometrics

• Movies – some fun

• R eferences – s ome more readings & links

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Biometrics

4

What is ?

• A term derived from ancient Greek

bio = lifemetric = to measure

• “Measurement of physiological and behavioral characteristics to automatically identify people.”

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Definitio

n

• “The automated approach to authenticate the identity of a person using the individual’s unique physiological or behavioral characteristics.” – Yau Wei Yun (2003)

• “Biometrics deals with identification of individuals based on their biological or behavioral characteristics” – Jain et al (1999)

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Ch

ara

cteristics

• Physical/biological characteristics– Face – Fingerprint – DNA – Hand and finger geometry – Eye structure – Iris – Retina – Ear – Vascular patterns – Odor– Voiceprint

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Ch

ara

cteristics

• Behavioral characteristics– Signature – Gait – Handwriting – Keystroke – Voice pattern

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Iden

tifica

tion

• Identification – associating an identity with an individual

• Verification (authentication)– The problem of confirming or denying a

person’s claimed identity (1: 1)– Am I who I claim I am?

• Recognition (identification)– The problem of establishing a subject’s

identity (1: Many)– Who am I?

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Iden

tifica

tion M

eth

od

s

• Traditional– Something you know : PIN, password ...– Something you have: key, token, card...

But does not insure that you are here and the real owner .

• Biometrics – Something you are: a biometric.

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Applications

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Why u

se ?

• Accurate identification of a person could deter – crime and fraud– streamline business processes – save critical resources

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Who u

ses ?

• Government 

• Military 

• Schools 

• Commerce 

• Law Enforcement 

• Others ?

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Where

are

it use

d ?

• Many products such as PC are already using fingerprints .

• Another big class, historically the first, is the identification for police application .

• Now, some countries are using biometrics for immigration control in airport/border

patrol. • Banks are now proposing some ATMs.

• Payment using biometrics is more and more used in stores.

• Identification of the student in schools.• Identification of the mother/newborn in

hospitals.

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Operation

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Enrollment

CaptureCapture ProcessProcess StoreStore

How

does it w

ork ?

Verification

ProcessProcess

No MatchNo Match

MatchMatch

CaptureCapture

Compare

?

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Exam

ple

Original source : Anil Jain and Arun Ross (1999)

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Types

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Exam

ple

s

• Fingerprinting • Palm print• Iris scan • Retinal scan • Facial recognition • Voice recognition • Handwriting recognition • DNA

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Fingerp

rint

• Strength– Proven Technology Capable of High

Level of Accuracy– Range of Deployment Environments– Ergonomic, Easy-to-Use Device– Ability to Enroll Multiple Fingers

• Weakness– Inability to Enroll Some Users– Performance Deterioration over Time– Association with Forensic Application– Need to Deploy Specialized Devices

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Palm

prin

t

• Strength– Ability to Operate in Challenging

Environment– Established, Reliable Core Technology– General Perception as Non-intrusive– Relatively Stable Physiological

Characteristic as Basis– Combination of Convenience and

Deterrence

• Weakness– Inherently Limited Accuracy– Form Factor That Limits Scope of

Potential Applications– Price

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Iris

• Strength– Resistance to False Matching– Stability of Characteristic over Lifetime– Suitability for Logical and Physical

Access

• Weakness– Difficulty of Usage– False Non-matching and Failure-to-

Enroll– User Discomfort with Eye-Based

Technology– Need for a Proprietary Acquisition

Device

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Retin

a

• Strength– it is not easy to change or replicate the

retinal vasculature.– Supposed to be the most secure

biometric

• Weakness– The image acquisition involves

cooperation of the subject– entails contact with the eyepiece– requires a conscious effort on the part

of the user.

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Face

• Strength– Ability to Leverage Existing Equipment

and Image Processing– Ability to Operate without Physical

Contact or User Complicity– Ability to Enroll Static Images

• Weakness– Acquisition Environment Effect on

Matching Accuracy– Changes in Physiological Characteristics

That Reduce Matching Accuracy– Potential for Privacy Abuse Due to Non-

cooperative Enrollment and Identification

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Voice

• Strength– Ability to Leverage Existing Telephony

Infrastructure– Synergy with Speech Recognition and

Verbal Account Authentication– Resistance to Imposters– Lack of Negative Perceptions

Associated with Other Biometrics

• Weakness– Effect of Acquisition Devices and

Ambient Noise on Accuracy– Perception of Low Accuracy– Lack of Suitability for Today’s PC Usage

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Sig

natu

re

• Strength– Resistant to Imposters– Leverages Existing Processes– Perceived as Non-invasive– Users Can Change Signatures

• Weakness– Inconsistent Signatures Lead to

Increased Error Rates– Users Unaccustomed to Singing on

Tablets– Limited Applications

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DN

A

• DNA (DeoxyriboNucleic Acid) is the 1D ultimate unique code for one’s individuality.

• Identification for forensic applications only.

• Three factors limit the utility of this biometric for other applications– Contamination and sensitivity– Automatic real-time identification

issues– Privacy issues

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Issues

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Com

pariso

n

• Universality – each person should have the characteristic.

• Uniqueness – is how well the biometric separates individuals from another .

• Permanence – measures how well a biometric r esists aging.

• Collectability – ease of acquisition for measurement .

• Performance – accuracy, speed, and robustnes s of technology used.

• Acceptability – degree of approval of a technology .

• Circumvention – ease of use of a substitute.

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Com

pariso

n

Original source : Yau Wei Yun (2003)

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How

to ch

oose

?

• How to choose– Size of user group– Place of use and the nature of use– Ease of use and user training required– Error incidence such as due to age,

environment and health condition– Security and accuracy requirement

needed– User acceptance level, privacy and

anonymity– Long term stability including technology

maturity, standard, interoperability and technical support

– Cost

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Accu

racy

• Failure to Enroll Rate (FTE)– % of data input is considered invalid and fails to i

nput into the system.

• False Acceptance Rate (FAR) – % of invalid users who are incorrectly accepted

as genuine users.

• False Rejection Rate (FRR)– % of valid users who are rejected as imposters.

• Equal Error Rate (EER)– The rate at which both accept and reject error

are equal

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FTE

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Sco

res &

Th

resh

old

• scores – to express the similarity between a pattern and a biometric template .

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FAR

& FR

R

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Rela

tion

The more lower EER, the more accuracy

Original source : http://www.bioid.com/sdk/docs/About_EER.htm

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Con

cern

s

• Identify theft and privacy– Using two-factor solution – Biometrics are purely based on matching– Using encryption for matching template– Scanned live biometric data maybe

stolen

• Sociological concerns– Physical harm to an individual– Personal information through biometric

methods can be misused or sold

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Related to

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Exam

ple

• Database– Storing matching templates– Querying templates– Database management– Security issues

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Exam

ple

• Image processing– Assessing the quality– Enhancing the image

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Exam

ple

• Image processing

a) The originalb) A close-up of the originalc) After 1st stage of thinningd) After 2nd stage of thinninge) After applying algorithm,

showing bifurcations (black) and endpoints (grey)

Original source : http://www.ee.ryerson.ca/opr/research_projects/graph_fingerprint.html

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Exam

ple • Intelligent system

– Pattern classification & recognition– Decision rules

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Exam

ple

• Pattern classification & recognition– Training and testing data– Machine learning

Original source : Anil Jain and Arun Ross (1999)

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Exam

ple • Information retrieval

– Retrieval templates for recognition– Scoring– Evaluation

Recognition

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Movies

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Som

e fu

n

• Hollywood is using biometrics for years.

• some truth inside, but sometimes , it i s wrong…

• Must see– Gattaca (1997)

• It was wrong– The Island (2005)

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Som

e fu

n

• Others– James bond– The Bourne– Minority report– etc. (see the first website in reference)

• Use of some and public concerns• Physical biometric for identification

or authentication person is the most widely seen.

• Behavioral biometric much less

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References

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More

readin

gs &

links

Publications• Yun, Yau Wei. (2003) The ‘123 ’ of Biometric Technology.

- Retrieved from www.• Jain, Anil, Bolle, Ruud, and Pankanti, Sharath. (1999)

Introduction to biometrics. In: Biometrics, Personal Identification in Networked Society, pp. 1-41, Springer.

• Jain, Anil, and Ross, Arun. (1999) Introduction to biometrics. In: Handbook of Biometrics, pp

Lecture notes• Ioannis Pavlidis. (2003) Introduction to biometrics. In

course cosc6397. Department of Computer Science, University of Houston.

• Rawitat Pulum. (2006) Introduction to Biometrics. In course 510670. Faculty of Science, Silpakorn University.

Website• http://pagesperso-orange.fr/fingerchip/biometrics/

biometrics.htm• http://en.wikipedia.org/wiki/Biometrics• http://www.bioid.com/sdk/docs/About_EER.htm

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Rela

tion

50

Rela

tion

The more lower EER, the more accuracy