1. Introduction to Biometrics Dr. Pushkin Kachroo

2. New Field Face recognition from computer vision Speaker recognition from signal processing Finger prints from forensics and pattern recognition

3. Organization-1 Basics: –Core biometric concepts –General authentication protocols for Verification Identification Screening –Most common Finger, face, voice, iris, hand, signature, etc. Skin reflectance, gait, etc.

4. Organization-2 Performance and Selection –Fundamental measurable aspects affecting system accuracy –Realistic Error Rates System Issues –Overall design –Threat Models –Databases, APIs etc.

5. Organization-3 Mathematical Analyses –Analyses for Evaluation and Selection of Biometric System –Stochastic Methods –Optimzation (Error minimization)

6. Authentication Standard Methods: –ID cards, passports etc. –Problems: Misplaced, get lost, forged Automating identification

7. Biometrics Biometric Identification –Verification: (Easier) –Identification: (More difficult with large databases)

8. Applications Boarding an Aircraft Performing a financial transaction Picking up a child from daycare Office and home security

9. Distinct Personal Characteristics Physiological –Static Measurement –Fingerprint, hand geometry etc. Behavioral –Dynamic (temporal measurement) –Signature, gait, etc.

10. Person Authentication Three Traditional Modes –Possessions: keys, smart cards, passport etc. –Knowledge: Passwords, user ID, mother’s maiden name etc. –Biometrics: Physiological and Behavioral

11. Two Authentication Methods Verification: unique identifier which singles out a particular person (e.g. some I.D.) or person’s biometric. Identification: Compare with an entire database.

12. Desired Biometric Attributes Universality: Each person should have it Uniqueness: Each person different Permanence: Invariant over time Collectability: Sensors etc. Acceptability: Legally, socially etc.

13. Biometric Identifiers-1 Common: –Physiological: Face, fingerprint, hand geometry, Iris –Behavioral: Signature Voice

14. Biometric Identifiers-2 Used less (or emerging): –Physiological: DNA, Ear Shape, Odor,Retina, Skin Reflectance, Thermogram –Behavioral: Gait, keystroke, lip motion

15. Biometric Subsystems Biometric Readers (sensors) Feature Extractors Feature Matchers

16. Authentication Systems For Enrollment For Authentication

17. System Performance & Design Issues-1 System Accuracy –False Accept Rate (FAR) –False Reject Rate (FRR) Computation Speed –Scalability from small populations to large Exception Handling: –Failure to use (FTU), Failure to Enroll (FTE), Failure to Acquire (FTA), etc.

18. System Performance & Design Issues-2 System Cost Security Privacy Quantitative and qualitative parameters

19. Biometric Identification Reader, extractor, matcher (search in a database) –Positive Identification –Negative Identification

20. Biometric Verification Reader + I.D., extractor, Matching (with single) –Centralized databases –Distributed (e.g. smartcard stores the biometric features of the person)

21. Biometric Enrollment Positive Enrollment –Of people who match certain criteria for eligibility Negative –For non-eligibility

22. Biomeric System Security System Analyses Weakest point of failure Point failure verses dynamic