Dwork, C., C. Ilvento, G. N. Rothblum, and P. Sur. “Abstracting fairness: oracles, metrics, and interpretability.” 1st Symposium on Foundations of Responsible Computing, 2020. Download
Dwork, C., M. P. Kim, O. Reingold, G. N. Rothblum, and G. Yona. “Learning from outcomes: evidence-based rankings.” IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2019. Download
National Academies of Sciences, Engineering, Medicine. “Federal statistics, multiple data sources, and privacy protection: next steps.National Academies Press (2018). Download Slides.pdf
Dwork, C., and V. Feldman. “Privacy-preserving prediction.” In Conference on Learning Theory, 1693-1702, 2018, 1693-1702. Download
Dwork, C., and C. Ilvento. “Fairness under composition.10th Innovations in Theoretical Computer Science Conference (ITCS 2019). ITCS, Schloss Dagstuhl-Leibniz-Centrum-für-Informatik, 2018. Download
Bun, M., C. Dwork, G. N. Rothblum, and T. Steinke. “Composable and versatile privacy via truncated cdp.” Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, 2018, 74-86. Download
Dwork, C., A. Smith, T. Steinke, and J. Ullman. “Exposed! a survey of attacks on private data.” Annual Review of Statistics and Its Application 4 (2017): 61-84. Download
Dwork, C., F. Feldman, M. Hardt, T. Pitassi, O. Reingold, and A. L. Roth. “Preserving statistical validity in adaptive data analysis.” Proceedings of the 47th Annual ACM Symposium on Theory of Computing. STOC, 2015. DownloadAbstract
See also: Dwork, C., Feldman, V., Hardt, M., Pitassi, T., Reingold, O. and Roth, A., 2015. "The reusable holdout: Preserving validity in adaptive data analysis". Science, 349 (6248), pp. 636-638.
Zemel, R., Y. Wu, K. Swersky, T. Pitassi, and C. Dwork. “Learning fair representations.” Proceedings of the 30th International Conference on Machine Learning (PMLR), 2013, 28, 3, 325-333. Download
Dwork, C., M. Hardt, T. Pitassi, O. Reingold, and R. Zemel. “Fairness through awareness.” Proceedings of the 3rd Innovations in Theoretical Computer Science Conference (ITCS 12), 2012, 214-226. Download
Dwork, C., F. McSherry, K. Nissim, and A. Smith. “Calibrating noise to sensitivity in private data analysis.” Theory of Cryptography Conference , 2006, 265-284. DownloadAbstract

Notes: Appeared in Journal of Privacy and Confidentiality, 2016. 

Winner of 2017 Gödel Prize.

Dwork, C.Differential privacy.” International Colloquium on Automata, Languages, and Programming. ICALP, 2006. Download
Dolev, D., C. Dwork, and M. Naor. “Non-malleable cryptography.” SIAM Journal on Computing 30, no. 2 (2000). DownloadAbstract

Selected for SIAM Review 200345 (4), pp.727 -784.

Ajtai, M., and C. Dwork. “A public-key cryptosystem with worst-case/ average-case equivalence.” Proceedings of the 29th Annual ACM Symposium on Theory of Computing, 1997, 284-293. Download
Dwork, C., and M. Naor. “Pricing via processing or combatting junk mail.” Advances in Cryptology: CRYPTO 1992. Annual International Cryptography Conference, 1992. Download
Dolev, D., C. Dwork, and M. Naor. “Non-malleable cryptography.” Proceedings of the 23rd Annual ACM Symposium on Theory of Computing (STOC '91) (1991): 542-552. Download
Dwork, C., N. Lynch, and L. Stockmeyer. “Consensus in the presence of partial synchrony.” Journal of the ACM (JACM) 35, no. 2 (1988): 288-323. DownloadAbstract
Note: Winner of the 2007 Dijkstra Prize.