The aggregation and analysis of large transactional databases has become common in the commercial marketing industry. Government agencies are also interested in such aggregation and analysis but with a different goal: identifying suspicious behavior to prevent terrorism. Such analysis must, for legal reasons, respect the privacy of individuals and is more complicated than merely masking fields such as names or addresses. This talk with describe a variety of mathematical and computational problems that arise in protecting privacy during transactional database mining and analysis.
George Cybenko, Dorothy and Walter Gramm Professor of Engineering at Dartmouth, received his B.Sc. in mathematics at the University of Toronto, and an M.A. in mathematics and Ph.D. in applied mathematics from Princeton. He has taught on the computer science faculty at Tufts University and was professor of electrical engineering and computer science at the University of Illinois, Champaign-Urbana. He has served as editor for several mathematics, computer, and information theory publications, has helped organize dozens of conferences and symposia, and has published over one hundred journal papers, book chapters, and conference proceedings. An IEEE Fellow, he is a member of the IEEE Computer Society and SIAM. In November 2002, he was named founding editor-in-chief of IEEE Security & Privacy magazine.
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