Transcript Biometrics: Challenges and Applications

Biometrics: Challenges and
Applications
Department of
Computer Science
& Engineering
Ishwar K. Sethi
Department of Computer Science &
Engineering
Oakland University, Rochester, MI 48309
[email protected]
www.cse.secs.oakland.edu/isethi
iielab-secs.secs.oakland.edu
Biometrics – What is it?
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& Engineering
Technology for
automated
recognition or
verification of the
identity of a
person using
physiological or
behavioral
characteristics
such as
fingerprints, hand
geometry, iris,
voice, and
signatures.
Recognition vs.
Verification
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• Recognition or identification implies
checking whether a person is in the
system’s database or not. (one-tomany search)
• Verification or authentication
implies checking the identity claim
presented by a user. (one-to-one
search)
Why Biometrics?
•
–
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–
•
–
–
Better than
password/PIN
No need to
memorize
passwords
Requires physical
presence of the
person to be
identified
Better than
smart cards
Cannot be stolen
Cannot leave it at
home
Biometric System
Architecture
Enrollment Phase
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& Engineering
Data Capture &
Conditioning
Feature
Extraction
Template
Database
Template
Formation
Template
Matcher
Identification/Verification Phase
Data Capture &
Conditioning
Feature
Extraction
Template
Formation
Decision
Output
Processing Examples
Data Capture &
Conditioning
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Feature
Extraction
Fingerprint
Processing
Template
Formation
Retinal Scan
Processing
Data Capture &
Conditioning
Template
Formation
Feature
Extraction
An Example of a Face
Template
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Template Size
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Performance Measures
• False match rate (FMR)
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– How often the system will match a
subject with someone else’s template
• False non-match rate (FNMR)
– How often the system will fail to verify
a match when it does really exist
• Failure to enroll rate (FER)
– How often the system fails to enroll a
person because of the unacceptable
quality of the person’s biometric sample
State of the Art
Performance Metrics
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• False match rates have been falling
as the technology matures. Near
zero rates are possible with some
technologies
• False non-match rates lie in single
digit range
• Failure to enroll rates can be as high
as about 12%
Factors Affecting
Performance
• Data capture factors
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– Lighting, background noise, pose
etc.
• Sensor interoperability
• Temporal changes
– Facial hair, eye glasses etc.
• Segmentation error
Face Recognizer
Challenges
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& Engineering
Segmentation Error
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Biometric Applications (1)
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Computer Science
& Engineering
Biometric Applications (2)
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Computer Science
& Engineering
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Biometric Revenue Growth
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Market Share by
Technology
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Leading Biometric
Applications and Vertical
Markets
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Modality
Application
Key Vertical
Market
Fingerprint
Civil
Identification
Government
Face Recognition
Surveillance &
Screening
Travel &
Transportation
Hand Geometry
PC & Network
Security
Financial Sector
Middleware
Retail/ATM/POS Healthcare
Iris Recognition
Remote
Authentication
Source: International Biometric Group
Law
Enforcement
How Secure Are Biometric
Systems?
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& Engineering
Security system gets thumbs down from honours student
By CATRIONA JACKSON
Thursday, 13 June 2002
An ANU computer science student has fooled state-of-the-art thumbprint
security systems, and warned banks and business they aren't as secure as
they seem.
Australian National University honours student Chris Hill has proved that
"biometric" security systems, that use retina and fingerprint scanning to
identify people, could be fooled using the information stored inside the system
itself.
As part of his honours thesis, Mr Hill tried the theory out on a commercially
available system, and cracked it.
Defeating Spoofing of
Biometric Systems
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• Randomization of verification
data
• Retention of identifiable data
• Using multiple biometrics
• Using a combination of
biometrics and smart cards
Societal Issues (1)
• Are some people left out because of
physiological considerations
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& Engineering
– For example, about 3% of the population
has poor fingerprint quality
• Religious objections
– “Mark of the Beast” objection.
• Pat Robertson, host of “The 700 Club” and founder of
The Christian Broadcasting Network, Inc., observes
that the “Bible says the time is going to come when you
cannot buy or sell except when a mark is placed on your
hand or forehead.”
Societal Issues (2)
• Informational privacy
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– Function creep
– Tracking
– Identity theft
• Physical Privacy
– Stigmatization
– Hygiene
Function Creep
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& Engineering
• Function creep, or mission creep, is the process by
which the original purpose for obtaining the
information is widened to include purposes other
than the one originally stated. Function creep can
occur with or without the knowledge or agreement
of the person providing the data.
• Examples
– The use of SSN for purposes it was never intended
to is the best example of function creep.
– South Carolina sold photographs of the state’s
drivers to Image Data LLC, a New Hampshire
company.
Tracking
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• Possibility of linking different
transactions to build a profile
• Use of face recognition to
covertly monitor individuals
– Super Bowl in Tampa, Florida to
identify would be criminals and
terrorists
Identity Theft
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& Engineering
• Although the biometrics provide
a greater protection against the
identity theft, the remote
authentication does open up the
possibility of identity theft.
• Liveness/Spoofing
Privacy Risk Factors (1)
• Overt/Covert
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– Whether biometric signatures can be acquired
without users knowledge or not. Covert systems
are highly privacy invasive
• Optional/Mandatory
– Mandatory systems are considered more prone
to privacy risks
• Verification/Identification
– Systems with identification capabilities are
considered more risky
• Ownership of biometric data
– Systems where the biometric data resides with
the owner are less susceptible to privacy abuse
Privacy Risk Factors (2)
• Behavioral/Physiological
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Computer Science
& Engineering
– Behavioral biometric systems are less likely to
be employed in a privacy invasive manner
• Templates/Identifiable Data
– Systems that maintain identifiable data in
addition to templates are more risky
• Public/Private Sector
– Public sector use is more open to abuse due to
lax controls while private sector may be
tempted to share/link with others
Comparative Strengths of
Different Biometric
Technologies
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Summary
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• Biometrics is at the threshold of
tremendous growth. Numerous applications
are emerging. The war on terror has
hastened the deployment of biometrics
• Much hype in performance. Lots of
improvements are needed
• Template protection and methods against
spoofing are needed
• Privacy concerns need better addressing