This is the public, feature-limited version of the conference webpage. After Registration and login please visit the full version.

Adversarially Robust Streaming Algorithms via Differential Privacy

Avinatan Hasidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer

Oral presentation: Orals & Spotlights Track 10: Social/Privacy
on 2020-12-08T06:00:00-08:00 - 2020-12-08T06:15:00-08:00
Poster Session 2 (more posters)
on 2020-12-08T09:00:00-08:00 - 2020-12-08T11:00:00-08:00
Abstract: A streaming algorithm is said to be adversarially robust if its accuracy guarantees are maintained even when the data stream is chosen maliciously, by an adaptive adversary. We establish a connection between adversarial robustness of streaming algorithms and the notion of differential privacy. This connection allows us to design new adversarially robust streaming algorithms that outperform the current state-of-the-art constructions for many interesting regimes of parameters.

Preview Video and Chat

To see video, interact with the author and ask questions please use registration and login.