Aggregate query answering on anonymized tables

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2007, Pages 116-125

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

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF TORONTO   (Canada)

^c AT AND T LABS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AD HOC NETWORKS; ALGORITHMS; DATA PRIVACY; INFORMATION DISSEMINATION;

AD HOC ANALYSES; ANONYMIZATION; PRIVACY PROTECTION; UNDESIRABLE INFORMATION LEAKAGE;

QUERY PROCESSING;

EID: 34548710709     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2007.367857     Document Type: Conference Paper

References (14)

1. N. Adam, and J. Wortman. Security-Control Methods for Statistical Databases: A Comparative Study. ACM Computing Surveys, 21(4), 1989.
2. G. Aggarwal, T. Feder, K. Kenthapadi, R. Motwani, R. P. raby, D. Thomas, and A. Zhu. k-Anonymity: Algorithms and Hardness. Technical report, Stanford University, 2004.
3. R. Agrawal and R. Srikant. Privacy-Preserving Data Mining. In Proceedings of the ACM SIGMOD International Conference on Management of Data, Dallas, Texas, May 2000.
4. R. J. Bayardo and R. Agrawal. Data Privacy through Optimal k-Anonymization. In Proceedings of 21st IEEE International Conference on Data Engineering, Tokyo, Japan, Apr. 2005.
5. N. Koudas, D. Srivastava, T. Yu, and Q. Zhang. Aggregate Query Answering on Anonymized Tables. Technical Report TR-2006-16, North Carolina State University, 2006.
6. K. LeFevre, D. DeWitt, and R. Ramakrishnan. Incognito -Efficient Full-Domain K-Anonymity. In In Proceedings of ACM SIGMOD Conference, Baltimore, MD, June 2005.
7. N. Li, T. Li, and S. Venkatasubramanian. t-Closeness: Privacy Beyond k-Anonymity and ℓ-Diversity. In Proceedings of IEEE International Conference on Data Engineering, 2007.
8. A. Machanavajjhala, J. Gehrke, D. Kifer, and M. Venkitasubramaniam. ℓ-Diversity: Privacy Beyond k-Anonymity. In IEEE International Conference on Data Engineering, Atlanta, GA, Apr. 2006.
9. R. Moore. Controlled Data-Swapping Techniques for Masking Public Use Microdata Sets. Technical Report Statistical Research Division Report Series, RR 96-04, US Bureau of Census, 1996.
10. K. Muralidhar and R. Sarathy. Security of Random Data Perturbation Methods. ACM Transactions on Database Systems, 24(2), 1999.
11. L. Sweeney. Guaranteeing Anonymity When Sharing Medical Data, the Datafly System. Journal of the American Medical Informatics Association, pages 51-55, 1997.
12. U.C.Irvin Machine Learning Repository. http://www.ics.uci.edu/mearn/ mlrepository.html.
13. X. Xiao and Y. Tao. Anatomy: Simple and Effective Privacy Preservation. In International Conference on Very Large Data Bases, Seoul, Korea, Sept. 2006.
14. C. Yao, S. Wang, and S. Jajodia. Checking for k-Anonymity Violiation by Views. In International Conference on Very Large Data Bases, Trondheim, Norway, Aug. 2005.