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Volumn 21, Issue 2, 2009, Pages 206-219

K-anonymization with minimal loss of information

Author keywords

Approximation algorithms for NP hard problems; K anonymization; Privacy preserving data mining

Indexed keywords

AMOUNT OF INFORMATION; ANONYMIZATION; APPROXIMATION RATIOS; DATABASE ENTRY; GRAPH REPRESENTATION; HYPERGRAPH; INDIVIDUAL PRIVACY; K-ANONYMITY; K-ANONYMIZATION; NP-HARD; OPTIMAL SOLUTIONS; PERSONAL INFORMATION; PRIVACY-PRESERVING DATA MINING; RUNNING TIME; WILLIAMS;

EID: 69549119179     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2008.129     Document Type: Article
Times cited : (90)

References (28)
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  • 9
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  • 22
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    • Privacy preserving data mining
    • Y. Lindell and B. Pinkas, "Privacy Preserving Data Mining, " J. Cryptology, vol. 15, no. 3, pp. 177-206, 2002.
    • (2002) J. Cryptology , vol.15 , Issue.3 , pp. 177-206
    • Lindell, Y.1    Pinkas, B.2
  • 24
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    • Protecting respondent's privacy in microdata release
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    • Samarati, P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.