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학술지 Mitigating the ICA Attack Against Rotation-Based Transformation for Privacy Preserving Clustering
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저자
아지즈, 홍도원
발행일
200812
출처
ETRI Journal, v.30 no.6, pp.868-870
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.08.0208.0134
협약과제
08MK1100, 차세대 시큐리티 기술 개발, 조현숙
초록
The rotation-based transformation (RBT) for privacy preserving data mining is vulnerable to the independent component analysis (ICA) attack This paper introduces a modified multiple-rotation-based transformation technique for special mining applications, mitigating the ICA attack while maintaining the advantages of the RBT.
KSP 제안 키워드
Data mining(DM), Independent Component analysis, Privacy Preserving Data Mining(PPDM), Transformation technique, privacy preserving clustering(PPC)