Optimal Noise Adding Mechanisms for Approximate Differential Privacy

C. Dwork, F. McSherry, K. Nissim, and A. Smith, “Calibrating noise to sensitivity in private data analysis,” in Theory of Cryptography , ser. Lecture Notes in Computer Science, S. Halevi and T. Rabin, Eds. Springer Berlin / Heidelberg, 2006, vol. 3876, pp. 265–284

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 Proceedings of the 24th Annual International Conference on the Theory and Applications of Cryptographic Techniques , ser. EUROCRYPT ’06. Berlin, Heidelberg: Springer-Verlag, 2006, pp. 486–503

2006

Earlier work this paper cites.

K. Chaudhuri and N. Mishra, “When random sampling preserves privacy,” in Proceedings of the 26th annual international conference on Advances in Cryptology , ser. CRYPTO’06. Berlin, Heidelberg: Springer-Verlag, 2006, pp. 198–213

2006

Earlier work this paper cites.

K. Nissim, S. Raskhodnikova, and A. Smith, “Smooth sensitivity and sampling in private data analysis,” in Proceedings of the Thirty-Ninth annual ACM Symposium on Theory of Computing , ser. STOC ’07. New York, NY, USA: ACM, 2007, pp. 75–84

2007

Earlier work this paper cites.

F. McSherry and K. Talwar, “Mechanism design via differential privacy,” in Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science , ser. FOCS ’07. Washington, DC, USA: IEEE Computer Society, 2007, pp. 94–103

2007

Earlier work this paper cites.

C. Dwork, “Differential privacy: A survey of results,” in Proceedings of the 5th International Conference on Theory and Applications of Models of Computation , ser. TAMC’08. Berlin, Heidelberg: Springer-Verlag, 2008, pp. 1–19

2008

Earlier work this paper cites.

S. P. Kasiviswanathan and A. Smith, “A note on differential privacy: Defining resistance to arbitrary side information,” CoRR , vol. abs/0803.3946, 2008

Original

2008

Earlier work this paper cites.

A. Machanavajjhala, D. Kifer, J. Abowd, J. Gehrke, and L. Vilhuber, “Privacy: Theory meets practice on the map,” in Proceedings of the 2008 IEEE 24th International Conference on Data Engineering , ser. ICDE ’08. Washington, DC, USA: IEEE Computer Society, 2008, pp. 277–286

2008

Earlier work this paper cites.

C. Dwork and J. Lei, “Differential privacy and robust statistics,” in Proceedings of the 41st Annual ACM symposium on Theory of Computing , ser. STOC ’09. New York, NY, USA: ACM, 2009, pp. 371–380

2009

Earlier work this paper cites.

A. Ghosh, T. Roughgarden, and M. Sundararajan, “Universally utility-maximizing privacy mechanisms,” in Proceedings of the 41st Annual ACM Symposium on Theory of Computing , ser. STOC ’09. New York, NY, USA: ACM, 2009, pp. 351–360

2009

Cited alongside, same era.

C. Dwork, G. N. Rothblum, and S. Vadhan, “Boosting and differential privacy,” in Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science , ser. FOCS ’10. Washington, DC, USA: IEEE Computer Society, 2010, pp. 51–60

2010

Cited alongside, same era.

S. P. Kasiviswanathan, M. Rudelson, A. Smith, and J. Ullman, “The price of privately releasing contingency tables and the spectra of random matrices with correlated rows,” in Proceedings of the 42nd ACM Symposium on Theory of Computing , ser. STOC ’10. New York, NY, USA: ACM, 2010, pp. 775–784

2010

Cited alongside, same era.

H. Brenner and K. Nissim, “Impossibility of differentially private universally optimal mechanisms,” in Proceedings of the 51st Annual IEEE Symposium on Foundations of Computer Science , ser. FOCS ’10, Oct. 2010, pp. 71 –80

Q. Geng and P. Viswanath, “The optimal mechanism in differential privacy,” ArXiv e-prints , Dec. 2012

2012

Later among the works it cites.

A. De, “Lower bounds in differential privacy,” in Proceedings of the 9th International Conference on Theory of Cryptography , ser. TCC’12. Berlin, Heidelberg: Springer-Verlag, 2012, pp. 321–338

2012

Later among the works it cites.

C. Fang and E.-C. Chang, “Adaptive differentially private histogram of low-dimensional data,” in Privacy Enhancing Technologies , ser. Lecture Notes in Computer Science, S. Fischer-Hübner and M. Wright, Eds. Springer Berlin Heidelberg, 2012, vol. 7384, pp. 160–179

2012

Later among the works it cites.

J. Xu, Z. Zhang, X. Xiao, Y. Yang, and G. Yu, “Differentially private histogram publication,” in 2012 IEEE 28th International Conference on Data Engineering (ICDE) . IEEE, 2012, pp. 32–43

2012

Later among the works it cites.