Introduction to Biometrics
Dr. Pushkin Kachroo
New Field
• Face recognition from computer vision
• Speaker recognition from signal
processing
• Finger prints from forensics and pattern
recognition
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.
Organization-2
• Performance and Selection
– Fundamental measurable aspects affecting
system accuracy
– Realistic Error Rates
• System Issues
– Overall design
– Threat Models
– Databases, APIs etc.
Organization-3
• Mathematical Analyses
– Analyses for Evaluation and Selection of
Biometric System
– Stochastic Methods
– Optimzation (Error minimization)
Authentication
• Standard Methods:
– ID cards, passports etc.
– Problems:
• Misplaced, get lost, forged
• Automating identification
Biometrics
• Biometric Identification
– Verification: (Easier)
– Identification: (More difficult with large
databases)
Applications
•
•
•
•
Boarding an Aircraft
Performing a financial transaction
Picking up a child from daycare
Office and home security
Distinct Personal Characteristics
• Physiological
– Static Measurement
– Fingerprint, hand geometry etc.
• Behavioral
– Dynamic (temporal measurement)
– Signature, gait, etc.
Person Authentication
• Three Traditional Modes
– Possessions: keys, smart cards, passport
etc.
– Knowledge: Passwords, user ID, mother’s
maiden name etc.
– Biometrics: Physiological and Behavioral
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.
Desired Biometric Attributes
•
•
•
•
•
Universality: Each person should have it
Uniqueness: Each person different
Permanence: Invariant over time
Collectability: Sensors etc.
Acceptability: Legally, socially etc.
Biometric Identifiers-1
• Common:
– Physiological:
• Face, fingerprint, hand geometry, Iris
– Behavioral:
• Signature
• Voice
Biometric Identifiers-2
• Used less (or emerging):
– Physiological:
• DNA, Ear Shape, Odor,Retina, Skin Reflectance,
Thermogram
– Behavioral:
• Gait, keystroke, lip motion
Biometric Subsystems
• Biometric Readers (sensors)
• Feature Extractors
• Feature Matchers
Authentication Systems
• For Enrollment
• For Authentication
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.
System Performance & Design
Issues-2
• System Cost
• Security
• Privacy
• Quantitative and qualitative parameters
Biometric Identification
• Reader, extractor, matcher (search in a
database)
– Positive Identification
– Negative Identification
Biometric Verification
• Reader + I.D., extractor, Matching (with
single)
– Centralized databases
– Distributed (e.g. smartcard stores the
biometric features of the person)
Biometric Enrollment
• Positive Enrollment
– Of people who match certain criteria for
eligibility
• Negative
– For non-eligibility
Biomeric System Security
• System Analyses
• Weakest point of failure
• Point failure verses dynamic