Fetching the paper…
Reading the bibliography…
We initiate a study of the composition properties of interactive differentially private mechanisms.
Warner, S.L.: Randomized response: A survey technique for eliminating evasive answer bias. Journal of the American Statistical Association 60
1965
Earlier work this paper cites.
Feige, U., Shamir, A.: Zero knowledge proofs of knowledge in two rounds. In: Conference on the Theory and Application of Cryptology. pp. 526–544. Springer (1989)
1989
Earlier work this paper cites.
Canetti, R., Feige, U., Goldreich, O., Naor, M.: Adaptively secure multi-party computation. In: Proceedings of the twenty-eighth annual ACM symposium on Theory of computing. pp. 639–648 (1996)
1996
Earlier work this paper cites.
Goldreich, O., Krawczyk, H.: On the composition of zero-knowledge proof systems. SIAM Journal on Computing 25
1996
Earlier work this paper cites.
Dwork, C., Kenthapadi, K., McSherry, F., Mironov, I., Naor, M.: Our data, ourselves: Privacy via distributed noise generation. In: Annual International Conference on the Theory and Applications of Cryptographic Techniques. pp. 486–503. Springer (2006)
2006
Earlier work this paper cites.
Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating noise to sensitivity in private data analysis. In: Theory of cryptography conference. pp. 265–284. Springer (2006)
2006
Earlier work this paper cites.
Beimel, A., Nissim, K., Omri, E.: Distributed private data analysis: Simultaneously solving how and what. In: Annual International Cryptology Conference. pp. 451–468. Springer (2008)
2008
Earlier work this paper cites.
Dwork, C., Naor, M., Reingold, O., Rothblum, G.N., Vadhan, S.: On the complexity of differentially private data release: efficient algorithms and hardness results. In: Proceedings of the forty-first annual ACM symposium on Theory of computing. pp. 381–390 (2009)
2009
Earlier work this paper cites.
Dwork, C., Rothblum, G.N., Vadhan, S.: Boosting and differential privacy. In: 2010 IEEE 51st Annual Symposium on Foundations of Computer Science. pp. 51–60. IEEE (2010)
2010
Earlier work this paper cites.
Hardt, M., Rothblum, G.N.: A multiplicative weights mechanism for privacy-preserving data analysis. In: 2010 IEEE 51st Annual Symposium on Foundations of Computer Science. pp. 61–70. IEEE (2010)
2010
Cited alongside, same era.
Roth, A., Roughgarden, T.: Interactive privacy via the median mechanism. In: Proceedings of the forty-second ACM symposium on Theory of computing. pp. 765–774 (2010)
2010
Cited alongside, same era.
Kasiviswanathan, S.P., Lee, H.K., Nissim, K., Raskhodnikova, S., Smith, A.: What can we learn privately? SIAM Journal on Computing 40
2011
Cited alongside, same era.
Dwork, C., Roth, A., et al.: The algorithmic foundations of differential privacy. Foundations and Trends in Theoretical Computer Science 9
2014
Cited alongside, same era.
Kairouz, P., Oh, S., Viswanath, P.: The composition theorem for differential privacy. In: International conference on machine learning. pp. 1376–1385. PMLR (2015)
Mironov, I.: Rényi differential privacy. In: 2017 IEEE 30th Computer Security Foundations Symposium (CSF). pp. 263–275. IEEE (2017)
2017
Later among the works it cites.
Vadhan, S.: The complexity of differential privacy. In: Tutorials on the Foundations of Cryptography, pp. 347–450. Springer (2017)
2017
Later among the works it cites.
Bun, M., Dwork, C., Rothblum, G.N., Steinke, T.: Composable and versatile privacy via truncated cdp. In: Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing. pp. 74–86 (2018)
2018
Later among the works it cites.
Dong, J., Roth, A., Su, W.J.: Gaussian differential privacy. arXiv preprint arXiv:1905.02383 (2019)
2019
Later among the works it cites.
Goldreich, O.: Providing sound foundations for cryptography: on the work of Shafi Goldwasser and Silvio Micali. Morgan & Claypool (2019)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2015
Cited alongside, same era.
Bun, M., Steinke, T.: Concentrated differential privacy: Simplifications, extensions, and lower bounds. In: Theory of Cryptography Conference. pp. 635–658. Springer (2016)
2016
Cited alongside, same era.
Dwork, C., Rothblum, G.N.: Concentrated differential privacy. arXiv preprint arXiv:1603.01887 (2016)
2016
Cited alongside, same era.
Murtagh, J., Vadhan, S.: The complexity of computing the optimal composition of differential privacy. In: Theory of Computing. pp. 157–175. Theory of Computing (2016)
2016
Cited alongside, same era.
2019
Later among the works it cites.
2020
Later among the works it cites.
Gaboardi, M., Hay, M., Vadhan, S.: A programming framework for opendp (2020)
2020
Later among the works it cites.
Virtanen, P., Gommers, R., Oliphant, T.E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., et al.: Scipy 1.0: fundamental algorithms for scientific computing in python. Nature methods 17
2020
Later among the works it cites.