Keynote
Privacy Notions for Data Publishing and AnalysisDr. Ninghui Li 9:30am - 10:30am
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Abstract: Data collected by organizations and agencies are a key resource in today's information age. The use of sophisticated data mining techniques makes it possible to extract relevant knowledge that can then be used for a variety of purposes, such as research, developing innovative technologies and services, intelligence and counterterrorism operations, and providing inputs to public policy making. However the disclosure of those data poses serious threats to individual privacy. In this talk, we will present the evolvement of privacy notions for data publishing and analysis, leading to our proposed membership privacy framework, which formalizes the intuition that privacy means that the adversary cannot significantly increasing its ability to conclude that an entity is in the input dataset. We show that several recently proposed privacy notions, including differential privacy, are instantiations of the membership privacy framework, and that the framework provides a principled approach to developing new privacy notions under which better utility can be achieved than what is possible under differential privacy. Bio: Ninghui Li is a Professor of Computer Science at Purdue University. His research interests are in security and privacy. Prof. Li is currently Vice Chair of ACM Special Interest Group on Security, Audit and Control (SIGSAC) and Program Chair of 2014 ACM Conference on Computer and Communications Security (CCS). He is on the editorial boards of IEEE Transactions on Dependable and Secure Computing, Journal of Computer Security, and ACM Transactions on Internet Technology. Prof. Li received a Bachelor's degree from the University of Science and Technology of China in 1993 and a Ph.D. in Computer Science from New York University in 2000. Before joining the faculty of Purdue in 2003, he was a Research Associate at Stanford University Computer Science Department for 3 years. He is an ACM Distinguished Scientist and IEEE Senior Member. |