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Volumn 2006, Issue , 2006, Pages 754-759

(α, k)-anonymity: An enhanced k-anonymity model for privacy-preserving data publishing

Author keywords

Anonymity; Data mining; Data publishing; Privacy preservation

Indexed keywords

ANONYMITY MODEL; DATA DISTORTION; DATA PUBLISHING; PRIVACY PRESERVATION;

EID: 33749571958     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (597)

References (14)
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    • Fung, B.C.M.1    Wang, K.2    Yu, P.S.3
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    • L-diversity: Privacy beyond fc-anonymity
    • To appear
    • A. Machanavajjhala, J. Gehrke, and D. Kifer. l-diversity: privacy beyond fc-anonymity. In To appear in ICDE06, 2006.
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    • Machanavajjhala, A.1    Gehrke, J.2    Kifer, D.3
  • 9
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    • On the complexity of optimal k-anonymity
    • A. Meyerson and R. Williams. On the complexity of optimal k-anonymity. In PODS, pages 223-228, 2004.
    • (2004) PODS , pp. 223-228
    • Meyerson, A.1    Williams, R.2
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    • Template-based privacy preservation in classification problems
    • To appear
    • K. Wang, B. C. M. Fung, and P. S. Yu. Template-based privacy preservation in classification problems. In To appear in ICDM05, 2005.
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    • Wang, K.1    Fung, B.C.M.2    Yu, P.S.3
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    • Bottom-up generalization: A data mining solution to privacy protection
    • K. Wang, P. S. Yu, and S. Chakraborty. Bottom-up generalization: A data mining solution to privacy protection. In ICDM, pages 249-256, 2004.
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    • Wang, K.1    Yu, P.S.2    Chakraborty, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.