About the Presenter:

Lifeng Lai received the B.E. and M. E. degrees in Information Science and Electrical Engineering from Zhejiang University, Hangzhou, China in 2001 and 2004 respectively, and the PhD degree in Electrical and Computer  Engineering from The Ohio State University at Columbus, OH, in 2007. He is currently a postdoctoral research associate at the Department of Electrical Engineering, Princeton University. He was a Distinguished University Fellow of the Ohio State University from 2004 to 2007. He co-authored a paper that won the "Best Paper Award" from IEEE Global Communications Confe

About the Talk:

Biometric security systems have been widely deployed. A critical issue in biometric security systems is privacy: how to protect databases that store sensitive biological information? This question is particularly important, since there is no means to replace the compromised biology information that is an inherent and unchangeable property of each person. In this talk, I will present an analytical framework to study the security and privacy levels of any biometric security system. A fundamental tradeoff between privacy, measured by the normalized equivocation rate of the biometric measurements, and security, measured by the rate of the key generated from the biometric measurements, is identified. The scenario in which a potential attacker does not have side information is considered first. The privacy-security region, which characterizes the above-noted tradeoff is derived for this case. An important role of common information among random variables is revealed in perfect privacy biometric security systems. The scenario in which the attacker has side information is then considered. Inner and upper bounds on the privacy-security tradeoff are derived in this case.

Click here for seminar archive

Note: All MS thesis and PhD dissertation (proposal) defense are counted towards ECE791.