security challenges of biometric systems liam m. mayron, ph.d. arizona state university soda january...
TRANSCRIPT
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SECURITY CHALLENGES OF BIOMETRIC SYSTEMSLiam M. Mayron, Ph.D.
Arizona State University
SoDA
January 29, 2015
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Credit• Some of the reference material in this presentation is from
the textbook “Introduction to Biometrics” by Jain, Ross, and Nandakumar
• Some figures have been obtained from various online sources (as noted)
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Biometrics?• Biometrics are physical and behavioral characteristics that
uniquely identify humans• Typically used for authentication – associating individuals
with their personal identities• Active area of research – combines image processing,
security, information retrieval, physiology, cognitive science and other fields
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Harry PotterSource: http://allears.net/pl/fingerscan.htm
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Harry PotterSource: http://www.smartecarte.com/index.php?page=3000-series-lockers-more-information
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Harry PotterSource: http://gamingandbranding.blogspot.com/2011/08/universal-theme-park-in-orlando.html
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Identity What a person knows
What a person possesses
Who a person is
Relying on what a person knows and what a person possesses is not enough!
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Biometric functions
Verification
• “Are you who you say you are?”
Identification
• “Are you someone who the system previously recognized?”
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Examples of biometrics
Fingerprint Palm print Face Iris
Retina Ear Voice Signature
Gait Hand Vein Odor
DNA … AND MORE!
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FingerprintSource: http://www.vetmed.vt.edu/education/curriculum/vm8054/labs/lab14/IMAGES/FINGERPRINT.jpg
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IrisSource: http://en.wikipedia.org/wiki/File:NIRIris.png
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GaitSource: http://homepages.inf.ed.ac.uk/rbf/CVDICT/cvg.htm
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System operation
Enrollment phase
Store extracted features, discard the raw data
Extract features
Sample biometric data
Recognition phase
Determine user identity
Compare against stored data
Extract features
Re-sample biometric data
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System components
Drag picture to placeholder or click icon to add
Green: enrollment
Purple: recognitionSensor
Feature extractor
Database
Matcher
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Feature extraction• A lot of research interest!• Purpose is to generate a template, a compact
representation of a biometric trait• Assess quality• Segment data• Enhance data
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Matching• Compare query data to a previously stored template• Decide if a individual is a genuine match or an imposter• Exact matches are… suspicious
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Desired characteristics of biometrics
Uniqueness
• A biometric should be able to distinguish between two people
Permanence
• A biometric should not change (much) over time
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Design cycle
Understand nature of application and performance requirements
Choose appropriate biometric traits
Collect sample biometric data
Design or train the feature extractor or matcher
Evaluation and feedback
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Application considerations• Cooperative vs. non-cooperative users• Overt vs. covert deployment• Habituated vs. non-habituated users• Attended vs. unattended operation• Controlled vs. uncontrolled operation• Open vs. closed system
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Biometric considerations• Universality• Uniqueness• Permanence• Measurability• Performance• Acceptability• Circumvention
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Example: fingerprintsSource: http://en.wikipedia.org/wiki/File:Fingerprint_detail_on_male_finger.jpg
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Fingerprints• Ridges under our fingers allow us to grasp objects and
improve sensation• 20-24 ridges per centimeter is typical• Ridge flow is a result of random stresses during fetal
development*
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Fingerprints• The template of a fingerprint is derived from its minutiae• Minutiae consist of:
• Location: location in the image• Direction: direction along local ridge orientation• Type:
• Ending• Bifurcation
• A set of minutiae can potentially be used to derive the original ridge skeleton structure
• Sets of minutiae are compared. If the difference is within allowable parameters both are considered to match
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Security threats to biometric systems• Denial of Service (DoS)• Intrusion• Repudiation• Function creep
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System attacks
Insider attacks
• Biometric systems require human interaction – can be exploited• Collusion• Coercion• Negligence• Enrollment fraud• Exception abuse
Infrastructure attacks
• Combination of hardware and software
• Types • User interface• System modules• Interconnections• Template database
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User interface attacks
• Any attack initiated by presenting a biometric
• Impersonation• Obfuscation• Spoofing
• Spoof detection• Liveness detection• Measure physiological
properties• Pulse• Blood pressure• Perspiration• Spectral properties of the skin• Electrical conductivity• Skin deformation
• Identify voluntary/involuntary behavior
• Challenge-response
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Spoof detectionSource: http://www.engadget.com/2012/03/29/samsung-face-unlock-blinking-feature/
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Interconnection attacks• Man-in-the-middle attack• Replay attack• Hill-climbing
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Template database attacks• Leakage is a much more serious issue in biometric
systems than in password-based systems
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Leakage• Ways information about a biometric user can be learned
• Collusion or coercion: close proximity or cooperation• Covert acquisition: close proximity or cooperation• Brute force or hill-climbing: breach system security and intrusion• Template leakage: can be done remotely and anonymously
• It is not possible to replace compromised biometric tokens• The irrevocable nature of biometrics is both a strength
and a weakness
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Password security• Can techniques that are used to store passwords be used
to store biometric templates?• Encryption
• Security depends on the secrecy of the decryption key• Encryption (done simply) is not enough to secure passwords
• Password-based key generation• Password is never stored• Password is instead used to generate a cryptographic key
• Cryptographic hash• A one-way hash is applied• Cannot retrieve the original password from the hash*
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Requirements and challenges• Password security techniques cannot be directly applied
to biometric templates• Fundamental difference between biometric password systems• Password systems require an exact match• Biometric systems require a “good” match
• Biometric template protection requires• Cryptographic security: non-invertible templates• Performance: maintain matching ability• Revocability: generate multiple templates from the same data
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Encryption• Use encryption (AES, RSA) to secure template data• Not equivalent to password encryption
• Passwords are the same• Biometrics vary at each reading• Can compare encrypted passwords directly; cannot directly-
compare encrypted biometrics
• Disadvantage: original data is exposed during decryption• Advantage: matching performance is unaffected, can use
the same matching algorithms• Generally not sufficient for securing biometric data
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Feature transformation• A transformation function is applied to the template• Transformation function derived from a password or
random key• Can be invertible or non-invertible• Invertible
• Security is derived from the secrecy of the password or key• Keys can be user-specific• Homomorphic encryption
• Non-invertible• Equivalent to password hashing• More secure than invertible feature transformation• Challenging to create non-invertible transformation functions• Can adversely affect matching performance
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Biometric cryptosystems• Biometric data is used to bind or generate cryptographic
keys• Key binding: use biometric data to identify a key that was
generated independently of the biometric data itself• Key generation: use biometric data to create a key• Biometric cryptosystems are an area of active research• Helper information that is publicly available is used to
stabilize the system
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Discussion• There is no ideal method of biometric security• Many open challenges• Today, hybrids of multiple techniques are increasingly
common• Research topics to consider:
• Are there existing security methods that can be extended to biometrics?
• How can we measure the security of a biometric template database?
• Are there biometrics that are not compatible with existing security schemes?