Small domain randomization: Same privacy, more utility

Proceedings of the VLDB Endowment

Volumn 3, Issue 1, 2010, Pages 608-618

  Chaytor, Rhonda ^a   Wang, Ke ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; PROBABILITY; RANDOM PROCESSES;

EFFECTIVE SOLUTION; KEY ISSUES; LARGE DOMAIN; PRIVACY PRESERVING DATA MINING; PRIVACY PRESERVING DATA PUBLISHING; PRIVATE INFORMATION; RANDOM PERTURBATIONS; RANDOM VALUES;

DATA PRIVACY;

EID: 84859221764     PISSN: None     EISSN: 21508097     Source Type: Conference Proceeding    
DOI: 10.14778/1920841.1920919     Document Type: Article

References (24)

1. Aggarwal, C. C. and Yu, P. S. A condensation approach to privacy preserving data mining. EDBT'04.
2. Agrawal, R. and Srikant, R. Privacy-preserving data mining. SIGMOD'00.
3. Agrawal, R., Srikant R., and Thomas, D. Privacy preserving olap. SIGMOD'05.
4. Agrawal, S. and Haritsa, J. A framework for high-accuracy privacy preserving mining. ICDE'05.
5. Chen, B.-C., Ramakrishnan, R., and LeFevre, K. Privacy skyline: privacy with multidimensional adversarial knowledge. VLDB'07.
6. Chernoff, H. A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. Annals of Mathematical Statistics, 23, 4 (1952), 493-507.
7. Cuthill, E. and McKee, J. Reducing the bandwidth of sparse symmetric matrices. In Proc. of Nat. ACM Conf., 1969.
8. Du, W. and Zhan, Z. Using randomized response techniques for privacy preserving data mining. SIGKDD'03.
9. Evfimievski, A., Gehrke, J., and Srikant, R. Limiting privacy breaches in privacy preserving data mining. PODS'03.
10. Ghinita, G., Karras, P., Kalnis, P., and Mamoulis, N. Fast data anonymization with low information loss. VLDB'07.
11. Ghinita, G., Tao, Y., and Kalnis, P. On the anonymization of sparse high-dimensional data. ICDE'08.
12. Huang, Z. and Du, W. OptRR: optimizing randomized response schemes for privacy-preserving data mining. ICDE'08.
13. Koudas, N., Srivastava, D., Yu, T., and Zhang, Q. Aggregate query answering on anonymized tables. ICDE'07.
14. Li, T. and Li, N. Modeling and integrating background knowledge. ICDE'09.
15. Machanavajjhala, A., Gehrke, J., Kifer, D., and Venkitasubramaniam, M. l-diversity: privacy beyond kanonymity. ICDE'06.
16. McSherry, F. Privacy integrated queries: an extensible platform for privacy-preserving data analysis. SIGMOD'09.
17. Rastogi, V., Hong, S., and Suciu, D. The boundary between privacy and utility in data publishing. VLDB'07.
18. Reid, J. K. and Scott, J. A. Reducing the total bandwidth of a sparse unsymmetric matrix. SIAM J. Matrix Anal. Appl., 28, 3 (2006), 805-821.
19. Samarati, P. Protecting respondents' identities in microdata release. TKDE, 13, 6 (2001), 1010-1027.
20. Sweeney, L. Achieving k-anonymity privacy protection using generalization and suppression. Int'l J. on Uncert., Fuzz. and Knowledge-based Sys., 10, 5 (2002), 571-588.
21. Tao, Y., Xiao, X., Li, J., and Zhang, D. On anti-corruption privacy preserving publication. ICDE'08.
22. Warner, S. L. Randomized response: a survey technique for eliminating evasive answer bias. The A. Stat. Assoc., 60, 309 (1965), 63-69.
23. Xiao, X. and Tao, Y. Anatomy: simple and effective privacy preservation. VLDB'06.
24. Xiao, X., Tao, Y., and Chen, M. Optimal random perturbation at multiple privacy levels. VLDB'09.