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Assessment of disclosure risk is of paramount importance in the research and applications of data privacy techniques.
C. Dwork, F. McSherry, K. Nissim, and A. Smith, “Calibrating noise to sensitivity in private data analysis,” in Theory of cryptography . Springer, 2006, pp. 265–284
2006
Earlier work this paper cites.
C. Dwork, “Differential privacy,” in Proceedings of the International Colloquium on Automata, Languages and Programming (ICALP) . Springer-Verlag ARCoSS, 2006, pp. 1–12
2006
Earlier work this paper cites.
C. Dwork, K. Kenthapadi, F. McSherry, I. Mironov, and M. Naor, “Our data, ourselves: privacy via distributed noise generation,” in Advances in Cryptology: Proceedings of EUROCRYPT . Springer Berlin Heidelberg, 2006, pp. 485–503
2006
Earlier work this paper cites.
F. McSherry and K. Talwar, “Mechanism design via differential privacy,” in 48th Annual IEEE Symposium on Foundations of Computer Science , 2007, pp. 94–103
2007
Earlier work this paper cites.
K. Nissim, S. Raskhodnikova, and A. Smith, “Smooth sensitivity and sampling in private data analysis,” Proceedings of the 39th ACM Symposium on Theory of Computing , p. 75–84, 2007
2007
Earlier work this paper cites.
C. Dwork, “Differential privacy: A survey of results,” Theory and Applications of Models of Computation , vol. 4978, pp. 1–19, 2008
2008
Earlier work this paper cites.
A. Machanavajjhala, D. Kifer, J. Abowd, J. Gehrke, and L. Vilhuber, “Privacy: Theory meets practice on the map,” IEEE ICDE 24th International Conference , pp. 277 – 286, 2008
2008
Earlier work this paper cites.
F. McSherry, “Privacy integrated queries: an extensible platform for privacy-preserving data analysis,” in Proceedings of the 2009 ACM SIGMOD International Conference on Management of data . ACM, 2009, pp. 19–30
2009
Earlier work this paper cites.
C. Dwork and J. Lei, “Differential privacy and robust statistics,” Proceedings of the 41rd ACM symposium on Theory of computing , pp. 371–380, 2009
2009
Cited alongside, same era.
A. Roth and T. Roughgarden, “Interactive privacy via the median mechanism,” in Proceedings of the 42nd ACM Symposium on Theory of Computing , June 5-8, 2010
2010
Cited alongside, same era.
M. Hardt and K. Talwar, “On the geometry of differential privacy,” Proceedings of the Forty-second ACM Symposium on Theory of Computing, STOC ’10 , pp. 705–714, 2010
2010
Cited alongside, same era.
——, “Differential privacy,” in Encyclopedia of Cryptography and Security . Springer, 2011, pp. 338–340
2011
Cited alongside, same era.
M. Lichman, “UCI machine learning repository,” 2013. [Online]. Available: http://archive.ics.uci.edu/ml
2013
Later among the works it cites.
C. Dwork and A. Roth, The Algorithmic Foundation of Differential Privacy . Now Publishes, Inc., 2014
2014
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C. Dimitrakakis, B. Nelson, A. Mitrokotsa, and B. Rubinstein, “Robust and private bayesian inference,” in Algorithmic Learning Theory ALT 2014 , P. Auer, A. Clark, T. Zeugmann, and S. Zilles, Eds. Spring, Cham, 2014
2014
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2015
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2012
Cited alongside, same era.
A. Ghosh, T. Roughgarden, and M. Sundararajan, “Universally utility-maximizing privacy mechanisms,” SIAM Journal on Computing , vol. 41, no. 6, pp. 1673–1693, 2012
2012
Cited alongside, same era.
R. Hall, A. Rinaldoy, and L. Wasserman, “Random differential privacy,” Journal of Privacy and Confidentiality , vol. 4, no. 2, pp. 43–59, 2012
2012
Cited alongside, same era.
A.-S. Charest, “Empirical evaluation of statistical inference from differentially-private contingency tables,” in Proceeding of International Conferency on Privacy in Statistical Databases , 2012, pp. 257–272
2012
Cited alongside, same era.
2015
Later among the works it cites.
Q. Geng and P. Viswanath, “The optimal noise-adding mechanism in differential privacy,” IEEE Transactions on Information Theory , vol. 62, no. 2, pp. 925–951, 2016
2016
Closest in time.