Authentication: How Do I Know Who You Are?
of Computer Science and Engineering
variety of systems require reliable personal recognition schemes to either
confirm or determine the identity of an individual requesting their services.
The purpose of such schemes is to ensure that only a legitimate user, and not
anyone else, accesses the rendered services. Examples of such applications
include secure access to buildings, computer systems, laptops, cellular phones
and ATMs. Biometric recognition, or simply biometrics, refers to the automatic
recognition of individuals based on their physiological and/or behavioral
characteristics. Biometrics allows us to confirm or establish an individual’s
identity based on “who she is”, rather than by “what she possesses”
(e.g., an ID card) or “what she remembers” (e.g., a password). Current
biometric systems make use of fingerprints, hand geometry, iris, face, voice,
etc. to establish a person's identity. Biometric systems also introduce an
aspect of user convenience. For example, they alleviate the need for a user to
“remember” multiple passwords associated with different applications. A
biometric system that uses a single biometric trait for recognition has to
contend with problems related to non-universality of the trait, spoof attacks,
limited degrees of freedom, large intra-class variability, and noisy data. Some
of these problems can be addressed by integrating the evidence presented by
multiple biometric traits of a user (e.g., face and iris). Such systems, known
as multimodal biometric systems, demonstrate substantial improvement in
recognition performance. In this talk, we will present various applications of
biometrics, challenges associated in designing biometric systems, various fusion
strategies available to implement a multimodal biometric system and issues
related to securing the template and data encryption using biometric information.
Jain is a University Distinguished Professor in the Department of Computer
Science and Engineering at Michigan State University. He was the Department
Chair between 1995-99. His research interests include statistical pattern
recognition, exploratory pattern analysis, Markov random fields, texture
analysis, 3D object recognition, medical image analysis, document image analysis
and biometric authentication.
Several of his papers have been reprinted in edited volumes on image processing
and pattern recognition. He received the best paper awards in 1987 and 1991, and
received certificates for outstanding contributions in 1976, 1979, 1992, 1997
and 1998 from the Pattern Recognition Society. He also received the 1996 IEEE
Transactions on Neural Networks Outstanding Paper Award. He is a fellow of the
IEEE and International Association of Pattern Recognition (IAPR). He has
received a Fulbright Research Award, a Guggenheim
fellowship and the Alexander von Humboldt Research
Award. He delivered the 2002 Pierre
Devijver lecture sponsored by the International Association of Pattern
Recognition (IAPR). He holds six patents in the area of fingerprint matching.
His most recent book is Handbook
of Fingerprint Recognition, Springer 2003.