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Erschienen in:
2010 | OriginalPaper | Buchkapitel
A Survey on Preserving Privacy for Sensitive Association Rules in Databases
verfasst von : Chirag Modi, U. P. Rao, Dhiren R. Patel
Erschienen in: Information Processing and Management
Verlag: Springer Berlin Heidelberg
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Privacy preserving data mining (PPDM) is a novel research area to preserve privacy for sensitive knowledge from disclosure. Many of the researchers in this area have recently made effort to preserve privacy for sensitive knowledge in statistical database. In this paper, we present a detailed overview and classification of approaches which have been applied to knowledge hiding in context of association rule mining. We describe some evaluation metrics which are used to evaluate the performance of presented hiding algorithms.