Computation and Secrecy in Multiterminal Systems

nformation theoretic secrecy provides a framework for exploring schemes that guarantee provable unconditional security in network systems. This talk explores innate structural connections that exist between the information theoretic notion of multiterminal secrecy on the one hand and data compression and function computation on the other. For a setup where multiple terminals observe separate but correlated data and communicate over a public channel, three classes of secrecy problems are studied: (i) generating secret keys, (ii) ensuring secrecy against a querying eavesdropper, and (iii) secure function computation over an insecure communication network. The aforementioned connections lead to new results and algorithms for all of these problems. Applications abound, including in biometric security, hardware security, cloud computing and in-network computation in sensor networks. This talk is based on different joint works with Prakash Narayan, Piyush Gupta, Navin Kashyap, Yogesh Sankarasubramaniam and Kapali Viswanathan.

Biography: Himanshu Tyagi received his Bachelor of Technology degree in Electrical Engineering and Master of Technology degree in Communications and Information Technology, both from the Indian Institute of Technology, Delhi in 2007. His master 's thesis advisor was Prof. Ranjan K. Mallik. He is currently a doctoral candidate in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. His Ph.D. advisor is Prof. Prakash Narayan. He has interned at National Semiconductors, Bangalore in 2005, at Telecommunications Research Center Vienna, Vienna in 2006 (with Dr. Jossy Sayir), at Bell Labs, New Jersey in 2009 (with Dr. Piyush Gupta), and has spent a semester at Alfrèd Rènyi Institute of Mathematics in 2010 (with Prof. Imre Csiszár). He is a Clark School's Future Faculty Fellow (2010), and an ECE Distinguished Dissertation Fellow (2012) at the University of Maryland, College Park.  Also, he was a finalist for the best student paper award at the IEEE International Symposium on Information Theory (2010).