k-anonymity: A model for protecting privacy

International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems

Volumn 10, Issue 5, 2002, Pages 557-570

  Sweeney, Latanya ^a  

^a Carnegie Mellon University   (United States)

Author keywords

Data anonymity; Data fusion; Data privacy; Privacy; Re identification

Indexed keywords

DATA PRIVACY; DATA STRUCTURES; INFORMATION THEORY; MATHEMATICAL MODELS;

DATA ANONYMITY;

SECURITY OF DATA;

EID: 0036811662     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488502001648     Document Type: Article

References (25)

1. L. Sweeney, Uniqueness of Simple Demographics in the U.S. Population, LIDAP-WP4. Carnegie Mellon University, Laboratory for International Data Privacy, Pittsburgh, PA: 2000. Forthcoming book entitled, The Identifiability of Data.
2. National Association of Health Data Organizations, A Guide to State-Level Ambulatory Care Data Collection Activities (Falls Church: National Association of Health Data Organizations, Oct. 1996).
3. Group Insurance Commission testimony before the Massachusetts Health Care Committee. See Session of the Joint Committee on Health Care, Massachusetts State Legislature, (March 19, 1997).
4. Cambridge Voters List Database. City of Cambridge, Massachusetts. Cambridge: February 1997.
5. I. Fellegi. On the question of statistical confidentiality. Journal of the American Statistical Association, 1972, pp. 7-18.
6. J. Kim. A method for limiting disclosure of micro data based on random noise and transformation Proceedings of the Section on Survey Research Methods of the American Statistical Association, 370-374. 1986.
7. M. Palley and J. Siminoff. Regression methodology based disclosure of a statistical database Proceedings of the Section on Survey Research Methods of the American Statistical Association 382-387. 1986.
8. G. Duncan and R. Pearson. Enhancing access to data while protecting confidentiality: prospects for the future. Statistical Science, May, as Invited Paper with Discussion. 1991.
9. L. Willenborg and T. De Waal. Statistical Disclosure Control in Practice. Springer-Verlag, 1996.
10. T. Su and G. Ozsoyoglu. Controlling FD and MVD inference in multilevel relational database systems. IEEE Transactions on Knowledge and Data Engineering, 3:474-485, 1991.
11. M. Morgenstern. Security and Inference in multilevel database and knowledge based systems. Proc. of the ACM SIGMOD Conference, pages 357-373, 1987.
12. T. Hinke. Inference aggregation detection in database management systems. In Proc. of the IEEE Symposium on Research in Security and Privacy, pages 96-107, Oakland, 1988.
13. T. Lunt. Aggregation and inference: Facts and fallacies. In Proc. of the IEEE Symposium on Security and Privacy, pages 102-109, Oakland, CA, May 1989.
14. X. Qian, M. Stickel, P. Karp, T. Lunt, and T. Garvey. Detection and elimination of inference channels in multilevel relational database systems. In Proc. of the IEEE Symposium on Research in Security and Privacy, pages 196-205, 1993.
15. T. Garvey, T. Lunt and M. Stickel. Abductive and approximate reasoning models for characterizing inference channels. IEEE Computer Security Foundations Workshop, 4, 1991.
16. D. Denning and T. Lunt. A multilevel relational data model. In Proc. of the IEEE Symposium on Research in Security and Privacy, pages 220-234, Oakland, 1987.
17. D. Denning. Cryptography and Data Security. Addison-Wesley, 1982.
18. D. Denning, P. Denning, and M. Schwartz. Thetracker: A threat to statistical database security. ACM Trans. on Database Systems, 4(1):76-96, March 1979.
19. G. Duncan and S. Mukherjee. Microdata disclosure limitation in statistical databases: query size and random sample query control. In Proc. of the 1991 IEEE Symposium on Research in Security and Privacy, May 20-22, Oakland, California. 1991.
20. L. Sweeney. Guaranteeing anonymity when sharing medical data, the Datafly system. Proceedings, Journal of the American Medical Informatics Association. Washington, DC: Hanley & Belfus, Inc., 1997.
21. A. Hundepool and L. Willenborg. μ-and τ-argus: software for statistical disclosure control. Third International Seminar on Statistical Confidentiality. Bled: 1996.
22. L. Sweeney. Towards the optimal suppression of details when disclosing medical data, the use of sub-combination analysis. Proceedings, MEDINFO 98. International Medical Informatics Association. Seoul, Korea. North-Holland, 1998.
23. J. Ullman. Principles of Database and Knowledge Base Systems. Computer Science Press, Rockville, MD. 1988.
24. T. Dalenius. Finding a needle in a haystack-or identifying anonymous census record. Journal of Official Statistics, 2(3):329-336, 1986.
25. L. Sweeney, Computational Data Privacy Protection, LIDAP-WP5. Carnegie Mellon University, Laboratory for International Data Privacy, Pittsburgh, PA: 2000. Forthcoming book entitled, A Primer on Providing Privacy in Data.