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Title: Privacy preserving serial data publishing by role composition
Authors: Bu, Yingyi
Fu, Ada Wai-Chee
Wong, Raymond Chi-Wing
Chen, Lei
Li, Jiuyong
Keywords: Data mining
Serial publishing
Dynamic databases
Issue Date: 2008
Citation: Proceedings of the VLDB Endowment, v. 1, issue 1, August 2008, p. 845-856
Abstract: Previous works about privacy preserving serial data publishing on dynamic databases have relied on unrealistic assumptions of the nature of dynamic databases. In many applications, some sensitive values changes freely while others never change. For example, in medical applications, the disease attribute changes with time when patients recover from one disease and develop another disease. However, patients do not recover from some diseases such as HIV. We call such diseases permanent sensitive values. To the best of our knowledge, none of the existing solutions handle these realistic issues. We propose a novel anonymization approach called HD-composition to solve the above problems. Extensive experiments with real data confirm our theoretical results.
Rights: © ACM, 2008. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the VLDB Endowment, v. 1, issue 1, August 2008, p. 845-856.
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