Biometrics Presentation for EGMT 520 Ohio University

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Biometrics:

Biometrics Ohio University EMGT 520 Danijela Milosevic-Popovich 4-11-2011

OUTLINE:

OUTLINE What is Biometrics? Biometric Identifiers History of Biometrics Biometric Operating Modes Biometric Basic Operation Recognition Metrics/Errors Fingerprint Recognition Iris Recognition Facial Recognition Security Attacks Biometric Applications Biometric Vendors Biometric Market References

What is Biometrics?:

What is Biometrics? The term “biometrics” is derived from the Greek words “bio” ( life) and “metrics” (to measure). Biometrics is the science of establishing the identity of an individual based on the physical, chemical, or behavioral attributes of a person utilizing automated techniques

What is Biometrics?:

What is Biometrics? The security field uses 3 different types of identification : Something You Know — a password, PIN, or piece of personal information (such as your mother's maiden name) Something You Have — a card key, smart card, or token (like a SecureID card) Something You Are — a biometric Biometric = most secure and convenient authentication tool. It can't be shared/borrowed , stolen/lost, copied or forgotten

Biometric Identifiers:

Biometric Identifiers Classification of Biometric Identifiers Biological (Physiological) Characteristics: Eye irises and retinas Fingerprints Ears Face Recognition Palm Print Hand Geometry Vein Pattern Facial Thermogram Behavioral Characteristics: Signature Keystroke Dynamics Gait Voice Biological (Chemical Traces): Blood, Saliva, DNA, Odor

History of Biometrics:

History of Biometrics

Biometric Operating Modes:

Biometric Operating Modes Two Operating Modes: Verification  One to one comparison Identification  One to many comparison Enrollment

Biometric Operation:

Biometric Operation Five integrated components: Sensor  collects data and converts information to digital format Signal processing algorithms  quality control and develop biometric template Data storage  stores information Matching algorithm  compares to new templates to stored templates Decision process  automated or human assisted

Recognition Metrics/Errors:

Recognition Metrics/Errors Two types of recognition errors: False Acceptance Rate (FAR)  non matching pair of biometric data is wrongly accepted as a match by the system False Rejection Rate (FRR)  matching pair of biometric data is wrongly rejected by the system. FAR and FRR are complementary to one another Lowering one of the errors by varying the threshold, automatically increases the other error

Fingerprint Recognition:

Fingerprint Recognition Fingerprints consist of ridges and valleys on surface of the finger. Three basic patterns: Arch Loop Whorl Ridges from minutia points Right ending Bifurcation Short Ridge Two main algorithms of recognition Minutia matching Pattern matching

Fingerprint Recognition:

Fingerprint Recognition Issues Small areas Affected by cuts, dirt, and wear & tear People (surgeons, builders, special conditions) with no or few minutia points cannot use the system False minutia points due to low quality enrollment, imaging, fingerprint ridge detail. Benefits Easy to use Cheap Small footprint Low power Non-intrusive Large data base already available

Iris Recognition:

Iris Recognition Iris scan collects over 200 points of the iris such as furrows, freckles, and the corona. Glasses, contact lenses, and even eye surgery does not change the characteristics of the iris. To prevent an image / photo of the iris from being used instead of a real "live" eye, iris scanning systems will vary the light and check that the pupil dilates or contracts . Set of pixels transformed into a bit pattern preserving information for statistical comparison between two iris images…utilizing Daugman’s algorithms

Iris Recognition:

Iris Recognition Issues Relatively new technology Costlier than the fingerprint biometric technology Difficult to perform at distances > 2-3 meters Hoyos iris scanner scans an iris at a distance while person is in motion. Rate of one person/second. Susceptible to poor quality image Partially covered by eyelid and eyelashes Benefits Internal organ that is well protected against damage and wear Iris is mostly flat No need for person to be identified to touch any equipment Unprecedented false match rate

Face Recognition:

Face Recognition Facial recognition systems will measure and analyze overall structure, shape, and proportions of face: Distance between eyes, nose, mouth, and jaw edges Upper outline of eye sockets, sides of mouth, location of nose and eyes Area surrounding cheekbones At enrollment several pictures taken at slightly different angles and facial expressions Two main recognition algorithms: geometric and photometric Most commonly used algorithms: Principal Components Analysis, Linear Discriminant Analysis, and Elastic Bunch Graph Matching Three Dimensional face recognition Skin Texture Analysis

Face Recognition:

Face Recognition Issues Significant glare on eyeglasses or sunglasses Varying facial expressions Long hair obscuring the central part of the face Poor lighting that would cause the face to be over- or under-exposed Lack of resolution (too far away) More suited for verification, easy to change face proportion User perception, most people are uncomfortable with having their picture taken Benefits Not intrusive, can be done from a distance, without the user being aware 3-D facial recognition is not affected by changes in lighting or range of viewing angles, including a profile view

Security Attacks:

Security Attacks Presenting fake biometrics or a copy at the scanner Producing feature sets preselected by the intruder by overriding the feature extraction process Tampering with biometric feature presentation Attacking the channel between the stored templates and the matcher Corrupting the matcher Tampering with stored templates, either locally or remotely Overriding the match results

Biometric Vendors:

Biometric Vendors Top 10 Biometric Companies (2008) Nuance Communications Net Nanny (USA) Linguistic Data Consortium (LDC) Titan Corporation (USA) Securstar GmbH IDIAP Research Institute Bioscrypt Inc Bioenable Technologies ActivIdentity Inc. Cherry Corporation

Biometric Applications:

Biometric Applications Three main groups of applications Commercial Computer network login, electronic data security, e-commerce, Internet access, ATM or credit card use, physical access control, mobile phone, PDA, medical records management, distance learning Government applications National ID card, managing inmates in a correctional facility, driver’s license, social security, welfare disbursement, border control, passport control Forensic applications Corpse identification, criminal investigation, parenthood determination

Biometric Market:

Biometric Market Overall Market Statistics Market to double from $4,217.2 million in 2010 to $11,229.3 million in 2015 Estimated compound annual growth rate of 21.6% Automated Fingerprint Identification System is the leader of the biometric market $1.37 billion in 2010 will reach $3.28 billion in 2015 CAGR of 19% Iris, vein, and face market have expected CAGR of 27.5%, 25.4%, and 24.2%

References:

References http://www.biometrics.gov/default.aspx http://en.wikipedia.org/wiki/Biometrics http://www.biometricnewsportal.com/default.asp http://www.securityinfowatch.com/stanley-css-and-hoyos-corporation-announce-exclusive-partnership-deliver-iris-scanning-technology-so?pageNum=1 http://www.biometrics.org/ http://www.facebook.com/note.php?note_id=67941878293 http://news.cnet.com/2100-1001-915580.html http://www.ehow.com/facts_4898520_what-is-biometrics.html http://info.bioenabletech.com/Sales/news/biometrics-most-popular-company Jain, Anil K., Flynn, Patrick, & Ross, Arun A. (Eds.). ( 2008). Handbook of biometrics . New York, NY: Springer