Abstract:  Recent advances in biometric recognition and the increasing use of biometric data prompt significant privacy challenges associated with the possible misuse, loss, or theft of biometric data. There are legitimate reasons for biometric matching to be performed by two mutually distrustful parties, where due to privacy and liability considerations, neither party is willing to share its data. Alternatively, biometric experiments run by a single entity are often so large in scale that they are inevitably placed on an untrusted computational cloud or grid, where sensitive biometric data must also be protected. This gives rise to the need to develop secure computation and outsourcing techniques over biometric data where no information is revealed to the participants except the desired outcome of the computation and the outcome of the computation can be trusted. In this talk, I will
describe our recent results for securely comparing biometric images and outsourcing computation over biometric data in a robust manner. Most of the talk discusses techniques for private matching of iris codes.

Marina Blanton is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame. She received her Ph.D. in CS from Purdue University in 2007, MS in CS from Purdue University in 2004, and MS in EECS from Ohio University in 2002. Dr. Blanton's research interests lie in information security, privacy, and applied cryptography. She has over 40 research publications, is a co-editor of a recently published two-volume "Algorithms and Theory of Computation Handbook," and is
actively involved in professional service.