Biometric Authentication: How Do I Know Who You Are?

Anil K. Jain

Department of Computer Science and Engineering

Michigan State University


A wide 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.

 Anil 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.

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