Differential privacy and statistical disclosure risk measures: An investigation with binary synthetic data

Transactions on Data Privacy

Volumn 5, Issue 3, 2012, Pages 535-552

  McClure, David ^a   Reiter, Jerome P ^a  

^a Duke University   (United States)

Author keywords

Bayesian; Confidentiality; Disclosure; Risk; Synthetic

Indexed keywords

ASSESSMENT APPROACHES; BAYESIAN; CONFIDENTIALITY; DIFFERENTIAL PRIVACIES; DISCLOSURE; DISCLOSURE RISK; INTERPRETABILITY; OBSERVED DATA; POSTERIOR PROBABILITY; SPECIFIC VALUES; STATISTICAL DISCLOSURE; SYNTHETIC; SYNTHETIC DATA;

RISKS; SOFTWARE ENGINEERING;

DATA PRIVACY;

EID: 84871885755     PISSN: 18885063     EISSN: 20131631     Source Type: Journal    
DOI: None     Document Type: Article

References (22)

1. Abowd, J. and Vilhuber, L. (2008). How protective are synthetic data? In J. Domingo-Ferrer and Y. Saygun, eds., Privacy in Statistical Databases, 239-246. New York: Springer-Verlag.
2. Barak, B., Chaudhuri, K., Dwork, C., Kale, S., McSherry, F., and Talwar, K. (2007). Privacy, accuracy, and consistency too: a holistic solution to contingency table release. Proceedings of the 27th ACM SIGMOD International Conference on Management of Data / Principles of Database Systems.
3. Blum, A., Ligett, K., and Roth, A. (2008). A learning theory approach to non-interactive database privacy. Proceedings of the 40th ACM SIGACT Symposium on Thoery of Computing.
4. Caiola, G. and Reiter, J. P. (2010). Random forests for generating partially synthetic, categorical data. Transactions on Data Privacy 3, 27-42.
5. Charest, A. S. (2010). How can we analyze differentially private synthetic datasets. Journal of Privacy and Confidentiality 2:2, Article 3.
6. Drechsler, J., Bender, S., and R̈assler, S. (2008). Comparing fully and partially synthetic datasets for statistical disclosure control in the German IAB Establishment Panel. Transactions on Data Privacy 1, 105-130.
7. Drechsler, J. and Reiter, J. P. (2008). Accounting for intruder uncertainty due to sampling when estimating identification disclosure risks in partially synthetic data. In J. Domingo-Ferrer and Y. Saygin, eds., Privacy in Statistical Databases (LNCS 5262), 227-238. New York: Springer-Verlag.
8. Duncan, G. T. and Lambert, D. (1986). Disclosure-limited data dissemination. Journal of the American Statistical Association 81, 10-28.
9. Duncan, G. T. and Lambert, D. (1989). The risk of disclosure for microdata. Journal of Business and Economic Statistics 7, 207-217.
10. Dwork, C. (2006). Differential privacy. In 33rd International Colloquium on Automata, Languages, and Programming, part II, 1-12. Berlin: Springer.
11. Fienberg, S. E., Makov, U. E., and Sanil, A. P. (1997). ABayesian approach to data disclosure: Optimal intruder behavior for continuous data. Journal of Official Statistics 13, 75-89.
12. Kinney, S. K., Reiter, J. P., Reznek, A. P., Miranda, J., Jarmin, R. S., and Abowd, J. M. (2011). Towards unrestricted public use business microdata: The synthetic Longitudinal Business Database. International Statistical Review 79, 363-384.
13. Machanavajjhala, A., Kifer, D., Abowd, J., Gehrke, J., and Vilhuber, L. (2008). Privacy: Theory meets practice on the map. In IEEE 24th International Conference on Data Engineering, 277-286.
14. Raghunathan, T. E., Reiter, J. P., and Rubin, D. B. (2003). Multiple imputation for statistical disclosure limitation. Journal of Official Statistics 19, 1-16.
15. Reiter, J. P. (2005a). Estimating identification risks in microdata. Journal of the American Statistical Association 100, 1103-1113.
16. Reiter, J. P. (2005b). Releasing multiply-imputed, synthetic public use microdata: An illustration and empirical study. Journal of the Royal Statistical Society, Series A 168, 185-205.
17. Reiter, J. P. and Mitra, R. (2009). Estimating risks of identification disclosure in partially synthetic data. Journal of Privacy and Confidentiality 1, 99-110.
18. Reiter, J. P. and Raghunathan, T. E. (2007). The multiple adaptations of multiple imputation. Journal of the American Statistical Association 102, 1462-1471.
19. Rubin, D. B. (1993). Discussion: Statistical disclosure limitation. Journal of Official Statistics 9, 462-468.
20. Sarathy, R. and Muralidhar, K. (2011). Evaluating Laplace noise addition to satisfy differential privacy for numeric data. Transactions on Data Privacy 4, 1-17.
21. Skinner, C. J. and Shlomo, N. (2008). Assessing identification risk in survey microdata using log-linear models. Journal of the American Statistical Association 103, 989-1001.
22. Wasserman, L. and Zhou, S. (2010). A statistical framework for differential privacy. Journal of the American Statistical Association 105, 375-389.