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학술대회 Privacy Preserving Association Rule Ming Revisited
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저자
아지즈, 홍도원
발행일
200809
출처
World Conference on Information Security Applications (WISA) 2008, pp.1-15
초록
Privacy preserving association rule mining algorithms have been designed for discovering the relations between variables in data while maintaining the data privacy. In this article we revise one of the recently introduced schemes for association rule mining using fake transactions (FS). In particular, our analysis shows that the FS scheme has exhaustive storage and high computation requirements for guaranteeing a reasonable level of privacy. We introduce a realistic definition of privacy that benefits from the average case privacy and motivates the study of a weakness in the structure of FS by fake transactions filtering. In order to overcome this problem, we improve the FS scheme by presenting a hybrid scheme that considers both privacy and resources as two concurrent guidelines. Analytical and empirical results show the efficiency and applicability of our proposed scheme. Copyright ⓒ2010 The Institute of Electronics, Information and Communication Engineers.
KSP 제안 키워드
Association rule mining algorithms, Hybrid Scheme, Information and communication, Privacy Preserving Association Rule Mining(PPAM), data privacy