Invited Talk by Hillol Kargupta
Multi-Party Privacy Preserving Distributed Data Mining: A Game Theoretic Perspective
Analyzing privacy-sensitive data in a multi-party environment often assumes that the parties are well-behaved, abiding by the protocols as expected. Parties compute whatever is needed, communicate correctly following the rules, and do not collude with other parties for exposing third party sensitive data. This talk will argue that most of these nice assumptions fall apart in real-life applications of privacy-preserving distributed data mining (PPDM). The talk will offer a more realistic formulation of the PPDM problem as a multi-party game where each party tries to maximize its own objective or utility. The talk will develop a game-theoretic framework and discuss some recent results. It will also discuss equilibrium-analysis of such games and describe some local distributed algorithms that are based on such game theoretic frameworks.
Hillol Kargupta is an Associate Professor at the Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County. He received his Ph.D. in Computer Science from University of Illinois at Urbana-Champaign in 1996. He is also a co-founder of AGNIK LLC, a ubiquitous data intelligence company. His research interests include mobile and distributed data mining and computation in gene expression.
Dr. Kargupta won a National Science Foundation (NSF) CAREER award in 2001 for his research on ubiquitous and distributed data mining. His research is also funded by several other grants from NSF and NASA. He has received the best paper award in the 2003 IEEE International Conference on Data Mining. He also received support from the TRW Research Foundation, American Cancer Society, US Department of Energy, and Caterpillar. He won the 1997 Los Alamos Award for Outstanding Technical Achievement. His dissertation earned him the 1996 Society for Industrial and Applied Mathematics (SIAM) annual best student paper prize. He has published more than seventy five peer-reviewed articles in journals, conferences, and books. He is an associate editor of the IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Systems, Man, Cybernetics, Part B, among others. He is the co-editor of two books: (1) "Data Mining: Next Generation Challenges and Future Directions ", AAAI/MIT Press and (2) "Advances in Distributed and Parallel Knowledge Discovery", AAAI/MIT Press. He was the program-co-chair of the 2005 SIAM Data Mining Conference, Program vice-chair of 2005 PKDD Conference, Program vice-chair of 2005 IEEE International Data Mining Conference, Program Vice Chair for 2005 Euro-PAR Conference, Associate General Chair of the 2003 ACM SIGKDD Conference, and chair of the 2002 NSF Next Generation Data Mining Workshop among others. He is also in the organizing committee for the 2001, 2002, 2003, & 2004 SIAM Data Mining Conference, program committee for 2002 & 2003 IEEE Data Mining Conference, and the 2001 ACM SIGKDD Conference among several others. His other recent activities include hosting the 2001/2002/2003 High Performance, Pervasive, and Data Stream Mining workshops in SIAM Data Mining Conferences, ACM SIGKDD-2000 workshop on Distributed and Parallel Knowledge Discovery (DPKD), KDD-98 workshop on distributed data mining, a special issue on Distributed and Mobile Data Mining in the IEEE Transactions on Systems, Man, Cybernetics, Part B. He is currently editing a book entitled "Data Mining: Next Generation Challenges and Future Directions" which will be published by AAAI/MIT Press in 2003.