Adversarially Robust Streaming Algorithms via Differential Privacy
Data Structures and Algorithms
2020-04-14 v1 Machine Learning
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.
Cite
@article{arxiv.2004.05975,
title = {Adversarially Robust Streaming Algorithms via Differential Privacy},
author = {Avinatan Hassidim and Haim Kaplan and Yishay Mansour and Yossi Matias and Uri Stemmer},
journal= {arXiv preprint arXiv:2004.05975},
year = {2020}
}