Differentially private high-dimensional data publication via sampling-based inference

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2015-August, Issue , 2015, Pages 129-138

  Chen, Rui ^a   Xiao, Qian ^b   Zhang, Yu ^c   Xu, Jianliang ^c  

^a SAMSUNG RESEARCH AMERICA   (United States)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

Author keywords

Dependency graph; Differential privacy; High dimensional data; Joint distribution; Junction tree algorithm

Indexed keywords

APPROXIMATION ALGORITHMS; CLUSTERING ALGORITHMS; DATA MINING; DATA PRIVACY; FORESTRY; INFERENCE ENGINES; INTEGER PROGRAMMING;

DEPENDENCY GRAPHS; DIFFERENTIAL PRIVACIES; HIGH DIMENSIONAL DATA; JOINT DISTRIBUTIONS; JUNCTION TREE ALGORITHMS;

TREES (MATHEMATICS);

EID: 84954163825     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2783258.2783379     Document Type: Conference Paper

References (30)

1. G. Acs, C. Castelluccia, and R. Chen. Differentially private histogram publishing through lossy compression. In ICDM, 2012.
2. B. Barak, C. Dwork, S. Kale, F. McSherry, and K. Talwar. Privacy, accuracy, and consistency too: a holistic solution to contingency table release. In PODS, 2007.
3. Y. M. Bishop, S. E. Fienberg, and P. W. Paul. Discrete multivariate analysis. MIT Press, 1975.
4. G. Cormode, C. M. Procopiuc, D. Srivastava, and T. T. L. Tran. Differential private summaries for sparse data. In ICDT, 2012.
5. B. Ding, M. Winslett, J. Han, and Z. Li. Differentially private data cubes: optimizing noise sources and consistency. In SIGMOD, 2011.
6. C. Dwork, F. McSherry, K. Nissim, and A. Smith. Calibrating noise to sensitivity in private data analysis. In TCC, 2006.
7. M. R. Garey and D. S. Johnson. Computers and Intractability: a guide to the theory of NP-Completeness. W. H. Freeman, 1979.
8. M. Grant and S. Boyd. CVX: Matlab software for disciplined convex programming, version 2.1. http://cvxr.com/cvx, 2014.
9. M. Hardt, K. Ligett, and F. McSherry. A simple and practical algorithm for differentially private data release. In NIPS, 2012.
10. M. Hardt and G. N. Rothblum. A multiplicative weights mechanism for privacy-preserving data analysis. In FOCS, 2010.
11. J. Hartung, G. Knapp, and B. K. Sinha. Statistical meta-analysis with applications. John Wiley & Sons, 2008.
12. M. Hay, V. Rastogi, G. Miklau, and D. Suciu. Boosting the accuracy of differentially private histograms through consistency. PVLDB, 3(1):1021-1032, 2010.
13. I. F. Ilyas, W. Markl, P. Haas, P. Brown, and A. Aboulnaga. CORDS: Automatic discovery of correlations and soft functional dependencies. In SIGMOD, 2004.
14. G. D. Kleiter. The posterior probability of Bayes nets with strong dependences. Soft Computing, 3:162-173, 1999.
15. D. Koller and N. Friedman. Probabilistic graphical models: principles and techniques. MIT Press, 2009.
16. J. Lee and C. Clifton. Top-k frequent itemsets via differentially private FP-trees. In SIGKDD, 2014.
17. C. Li, M. Hay, G. Miklau, and A. McGregor. Optimizing linear counting queries under differential privacy. In PODS, 2010.
18. C. Li, M. Hay, G. Miklau, and Y. Wang. A data- and workload-aware query answering algorithm for range queries under differential privacy. PVLDB, 7(5):341-352, 2014.
19. N. Li, W. H. Qardaji, and D. Su. On sampling, anonymization, and differential privacy or, k-anonymization meets differentail privacy. In ASIACCS, 2012.
20. N. Mohammed, R. Chen, B. C. M. Fung, and P. S. Yu. Differentially private data release for data mining. In SIGKDD, 2011.
21. W. Qardaji, W. Yang, and N. Li. Priview: practical differentially private release of marginal contingency tables. In SIGMOD, 2014.
22. B. Rubinstein, P. L. Bartlett, L. Huang, and N. Taft. Learning in a large function space: privacy-preserving mechanisms for SVM learning. Journal of Privacy and Confidentiality, 4(1):65-100, 2012.
23. O. Williams and F. McSherry. Probabilistic inference and differential privacy. In NIPS, 2010.
24. X. Xiao, G. Wang, and J. Gehrke. Differential privacy via wavelet transform. In ICDE, 2010.
25. J. Xu, Z. Zhang, X. Xiao, and G. Yu. Differentially private histogram publicaiton. In ICDE, 2012.
26. G. Yaroslavtsev, G. Cormode, C. M. Procopiuc, and D. Srivastava. Accurate and efficient private release of datacubes and contingency tables. In ICDE, 2013.
27. G. Yuan, Z. Zhang, M. Winslett, X. Xiao, Y. Yang, and Z. Hao. Low-rank mechanism: optimizing batch queries under differential privacy. PVLDB, 5(11):1352-1363, 2012.
28. A. Yuille and A. Rangarajan. The concave-convex procedure. Neural Computation, 15(4):915-936, 2003.
29. J. Zhang, G. Cormode, C. M. Procopiuc, D. Srivastava, and X. Xiao. Privbayes: Private data release via bayesian networks. In SIGMOD, 2014.
30. X. Zhang, R. Chen, J. Xu, X. Meng, and Y. Xie. Towards accurate histogram publication under differential privacy. In SDM, 2014.