Distribution-based microdata anonymization

Proceedings of the VLDB Endowment

Volumn 2, Issue 1, 2009, Pages 958-969

  Koudas, Nick ^a   Yu, Ting ^b   Srivastava, Divesh ^c   Zhang, Qing ^d  

^a UNIVERSITY OF TORONTO   (Canada)

^b NORTH CAROLINA STATE UNIVERSITY   (United States)

^c AT AND T LABS RESEARCH   (United States)

^d TERADATA CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGGREGATE ANALYSIS; AGGREGATE QUERIES; ANONYMIZATION; DATA DISTORTION; MICRODATA ANONYMIZATION; NOVEL METHODOLOGY; PRIVACY MODELS; SENSITIVE ATTRIBUTE;

METADATA;

EID: 78649333205     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/1687627.1687735     Document Type: Article

References (17)

1. J. Brickell and V. Shmatikov. The cost of privacy: destruction of data-mining utility in anonymized data publishing. In KDD, 2008.
2. J.-W. Byun, Y. Sohn, E. Bertino, and N. Li. Secure anonymization for incremental datasets. In SDM, 2006.
3. G. Cormode, D. Srivastava, T. Yu, and Q. Zhang. Anonymizing bipartite graph data using safe groupings. In VLDB, 2008.
4. M. Hay, G. Miklau, D. Jensen, D. F. Towsley, and P.Weis. Resisting structural re-identification in anonymized social networks. In VLDB, 2008.
5. K. LeFevre, D. DeWitt, and R. Ramakrishnan. Incognito - efficient full-domain k-anonymity. In SIGMOD, 2005.
6. N. Li, T. Li, and S. Venkatasubramanian. t -closeness:privacy beyond k-anonymity and l-diversity. In ICDE, 2007.
7. A. Machanavajjhala, J. Gehrke, D. Kifer, and M. Venkitasubramaniam. l-diversity: privacy beyond k-anonymity. In ICDE, 2006.
8. D. J. Martin, D. Kifer, A. Machanavajjhala, J. Gehrke, and J. Y. Halpern. Worst-case background knowledge for privacy-preserving data publishing. In ICDE, 2007.
9. P. Samarati. Protecting respondent's privacy in microdata release. IEEE Transactions on Knowledge and Data Engineering, 13(6):1010?1027, 2001.
10. L. Sweeney. Guaranteeing anonymity when sharing medical data, the datafly system. Journal of the American Medical Informatics Association, pages 51-55, 1997.
11. L. Sweeney. Achieving k-anonymity privacy protection using generalization and suppression. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, 10(5):571?588, 2002.
12. U.C.Irvin Machine Learning Repository. http://www.ics.uci.edu/~mlearn/mlrepository.html.
13. X. Xiao and Y. Tao. Anatomy: simple and effective privacy preservation. In VLDB, 2006.
14. X. Xiao and Y. Tao. M-invariance: towards privacy preserving re-publication of dynamic datasets. In SIGMOD, 2007.
15. X. Xiao and Y. Tao. M-invariance: towards privacy preserving re-publication of dynamic datasets. In SIGMOD, 2007.
16. Q. Zhang, N. Koudas, D. Srivastava, and T. Yu. Aggregate query answering on anonymized tables. In ICDE, 2007.
17. B. Zhou and J. Pei. Preserving privacy in social networks against neighborhood attacks. In ICDE, 2008.