Epsilon*: Privacy Metric for Machine Learning Models

no code implementations • 21 Jul 2023 • Diana M. Negoescu, Humberto Gonzalez, Saad Eddin Al Orjany, Jilei Yang, Yuliia Lut, Rahul Tandra, Xiaowen Zhang, Xinyi Zheng, Zach Douglas, Vidita Nolkha, Parvez Ahammad, Gennady Samorodnitsky

We introduce Epsilon*, a new privacy metric for measuring the privacy risk of a single model instance prior to, during, or after deployment of privacy mitigation strategies.

Inference Attack Membership Inference Attack

Privately detecting changes in unknown distributions

no code implementations • ICML 2020 • Rachel Cummings, Sara Krehbiel, Yuliia Lut, Wanrong Zhang

Much of the prior work on change-point detection---including the only private algorithms for this problem---requires complete knowledge of the pre-change and post-change distributions.

Change Point Detection