SECURITY CHALLENGES OF BIOMETRIC SYSTEMSLiam M. Mayron, Ph.D.

Arizona State University

SoDA

January 29, 2015

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)

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

Harry PotterSource: http://allears.net/pl/fingerscan.htm

Harry PotterSource: http://www.smartecarte.com/index.php?page=3000-series-lockers-more-information

Harry PotterSource: http://gamingandbranding.blogspot.com/2011/08/universal-theme-park-in-orlando.html

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!

Biometric functions

Verification

• “Are you who you say you are?”

Identification

• “Are you someone who the system previously recognized?”

Examples of biometrics

Fingerprint Palm print Face Iris

Retina Ear Voice Signature

Gait Hand Vein Odor

DNA … AND MORE!

FingerprintSource: http://www.vetmed.vt.edu/education/curriculum/vm8054/labs/lab14/IMAGES/FINGERPRINT.jpg

IrisSource: http://en.wikipedia.org/wiki/File:NIRIris.png

GaitSource: http://homepages.inf.ed.ac.uk/rbf/CVDICT/cvg.htm

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

System components

Drag picture to placeholder or click icon to add

Green: enrollment

Purple: recognitionSensor

Feature extractor

Database

Matcher

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

Matching• Compare query data to a previously stored template• Decide if a individual is a genuine match or an imposter• Exact matches are… suspicious

Desired characteristics of biometrics

Uniqueness

• A biometric should be able to distinguish between two people

Permanence

• A biometric should not change (much) over time

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

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

Biometric considerations• Universality• Uniqueness• Permanence• Measurability• Performance• Acceptability• Circumvention

Example: fingerprintsSource: http://en.wikipedia.org/wiki/File:Fingerprint_detail_on_male_finger.jpg

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*

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

Security threats to biometric systems• Denial of Service (DoS)• Intrusion• Repudiation• Function creep

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

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

Spoof detectionSource: http://www.engadget.com/2012/03/29/samsung-face-unlock-blinking-feature/

Interconnection attacks• Man-in-the-middle attack• Replay attack• Hill-climbing

Template database attacks• Leakage is a much more serious issue in biometric

systems than in password-based systems

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

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*

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

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

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

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

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?

THANK YOU!Questions? lmayron@asu.edu or stop by BYENG 506