Information preservation in statistical privacy and Bayesian estimation of unattributed histograms

Proceedings of the ACM SIGMOD International Conference on Management of Data

Volumn , Issue , 2013, Pages 677-688

  Lin, Bing Rong ^a   Kifer, Daniel ^a  

^a PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Decision theory; Differential privacy; Privacy; Utility

Indexed keywords

BAYESIAN DECISION MAKER; BAYESIAN DECISION THEORY; DIFFERENTIAL PRIVACIES; INFORMATION PRESERVATIONS; MEASURE OF INFORMATION; POSTPROCESSING ALGORITHMS; STATISTICAL INFORMATION; UTILITY;

ALGORITHMS; BAYESIAN NETWORKS; DATA PRIVACY; DECISION MAKING; DECISION THEORY; QUERY PROCESSING; STATISTICAL METHODS;

GRAPHIC METHODS;

EID: 84880543792     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2463676.2463721     Document Type: Conference Paper

References (49)

1. John M. Abowd and Simon D. Woodcock. Disclosure limitation in longitudinal linked data. Confidentiality, Disclosure, and Data Access: Theory and Practical Applications for Statistical Agencies, pages 215-277, 2001.
2. Nabil Adam and John Worthmann. Security-control methods for statistical databases. ACM Computing Surveys, 21(4):515-556, 1989.
3. Charu C. Aggarwal. On unifying privacy and uncertain data models. In ICDE, 2008.
4. Mário S. Alvim, Miguel E. Andrés, Konstantinos Chatzikokolakis, Pierpaolo Degano, and Catuscia Palamidessi. Differential privacy: on the trade-off between utility and information leakage. http://arxiv.org/abs/1103.5188, 2011.
5. Mário S. Alvim, Miguel E. Andrés, Konstantinos Chatzikokolakis, and Catuscia Palamidessi. On the relation between differential privacy and quantitative information flow. In ICALP, 2011.
6. Mina Askari, Reihaneh Safavi-Naini, and Ken Barker. An information theoretic privacy and utility measure for data sanitization mechanisms. In CODASPY, 2012.
7. Boaz Barak, Kamalika Chaudhuri, Cynthia Dwork, Satyen Kale, Frank McSherry, and Kunal Talwar. Privacy, accuracy and consistency too: A holistic solution to contingency table release. In PODS, 2007.
8. R. E. Barlow, D. J. Bartholomew, J. M. Bremner, and H. D. Brunk. Statistical Inference Under Order Restrictions. John Wiley and Sons, 1972.
9. Christopher M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.
10. Avrim Blum, Cynthia Dwork, Frank McSherry, and Kobbi Nissim. Practical privacy: the SuLQ framework. In PODS, pages 128-138, 2005.
11. Avrim Blum, Katrina Ligett, and Aaron Roth. A learning theory approach to non-interactive database privacy. In STOC, pages 609-618, 2008.
12. Stephen Boyd and Lieven Vandenberghe. Convex Optimization. Cambridge University Press, New York, NY, USA, 2004.
13. Bee-Chung Chen, Daniel Kifer, Kristen LeFevre, and Ashwin Machanavajjhala. Privacy-preserving data publishing. Foundations and Trends in Databases, 2(1-2):1-167, 2009.
14. Bolin Ding, Marianne Winslett, Jiawei Han, and Zhenhui Li. Differentially private data cubes: optimizing noise sources and consistency. In SIGMOD, 2011.
15. Irit Dinur and Kobbi Nissim. Revealing information while preserving privacy. In PODS, 2003.
16. Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. Calibrating noise to sensitivity in private data analysis. In TCC, 2006.
17. Cynthia Dwork, Moni Naor, Omer Reingold, Guy N. Rothblum, and Salil Vadhan. On the complexity of differentially private data release: Efficient algorithms and hardness results. In STOC, 2009.
18. Alexandre Evfimievski, Ramakrishnan Srikant, Rakesh Agrawal, and Johannes Gehrke. Privacy preserving mining of association rules. In KDD, 2002.
19. B. C. M. Fung, K. Wang, R. Chen, and P. S. Yu. Privacy-preserving data publishing: A survey on recent developments. ACM Computing Surveys, 42(4), 2010.
20. A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin. Bayesian Data Analysis. Chapman & Hall/CRC, 2nd edition, 2003.
21. Arpita Ghosh and Aaron Roth. Selling privacy at auction. In EC, 2011.
22. Arpita Ghosh, Tim Roughgarden, and Mukund Sundararajan. Universally utility-maximizing privacy mechanisms. In STOC, 2009.
23. Mangesh Gupte and Mukund Sundararajan. Universally optimal privacy mechanisms for minimax agents. In PODS, 2010.
24. M. Hay, V. Rastogi, G. Miklau, and D. Suciu. Boosting the accuracy of differentially-private histograms through consistency. In VLDB, 2010.
25. Ali Inan, Murat Kantarcioglu, and Elisa Bertino. Using anonymized data for classification. In ICDE, 2009.
26. Vijay S. Iyengar. Transforming data to satisfy privacy constraints. In KDD, 2002.
27. Daniel Kifer and Bing-Rong Lin. Towards an axiomatization of statistical privacy and utility. In PODS, 2010.
28. Daniel Kifer and Bing-Rong Lin. An axiomatic view of statistical privacy and utility. Journal of Privacy and Confidentiality, 4(1), 2012.
29. Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, and Andrew McGregor. Optimizing linear counting queries under differential privacy. In PODS, 2010.
30. Chao Li, Daniel Yang Li, Gerome Miklau, and Dan Suciu. A theory of pricing private data. In ICDT, 2013.
31. Roderick J.A. Little. Statistical analysis of masked data. Journal of Official Statistics, 9(2):407-426, 1993.
32. Frank McSherry and Kunal Talwar. Mechanism design via differential privacy. In FOCS, 2007.
33. Frank D. McSherry. Privacy integrated queries: An extensible platform for privacy-preserving data analysis. In SIGMOD, pages 19-30, 2009.
34. Roger B. Myerson. Axiomatic foundations of bayesian decision theory. Technical Report 671, Northwestern University Center for Mathematical Studies in Economics and Management Science, 1986.
35. J. B. Paris. The Uncertain Reasoner's Companion. Cambridge University Press, 1994.
36. Davide Proserpio, Sharon Goldberg, and Frank McSherry. A workflow for differentially-private graph synthesis. In SIGCOMM Workshop on Online Social Networks, 2012.
37. L. Rabiner. A tutorial on hidden markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257-286, 1989.
38. T.E. Raghunathan, J.P. Reiter, and D.B. Rubin. Multiple imputation for statistical disclosure limitation. Journal of Official Statistics, 19:1-16, 2003.
39. Vibhor Rastogi, Dan Suciu, and Sungho Hong. The boundary between privacy and utility in data publishing. In VLDB, 2007.
40. J.P. Reiter. Using cart to generate partially synthetic public use microdata. Journal of Official Statistics, pages 441-462, 2005.
41. Tim Robertson and Paul Waltman. On estimating monotone parameters. Ann. Math. Statist., 39(3):1030-1039, 1968.
42. Tim Robertson and F. T. Wright. Algorithms in order restricted statistical inference and the cauchy mean value property. Ann. Statist., 8(3):645-651, 1980.
43. Leonard J. Savage. The Foundations of Statistics. Dover, 1972.
44. John von Neumann and Oskar Morgenstern. Theory of Games and Economic Behavior. Princeton University Press, 2007.
45. Larry Wasserman. All of Statistics: A Concise Course in Statistical Inference. Springer, 2003.
46. Oliver Williams and Frank McSherry. Probabilistic inference and differential privacy. In NIPS, 2010.
47. Raymond Wong, Ada Fu, Ke Wang, and Jian Pei. Minimality attack in privacy preserving data publishing. In VLDB, 2007.
48. Xiaokui Xiao and Yufei Tao. Anatomy: Simple and effective privacy preservation. In VLDB, 2006.
49. Qing Zhang, Nick Koudas, Divesh Srivastava, and Ting Yu. Aggregate query answering on anonymized tables. In ICDE, 2007.