Adversarially Robust Streaming Algorithms via Differential Privacy

Author:

Hassidim Avinatan1ORCID,Kaplan Haim2ORCID,Mansour Yishay2ORCID,Matias Yossi3ORCID,Stemmer Uri2ORCID

Affiliation:

1. Bar-Ilan University and Google, Tel Aviv, Israel

2. Tel Aviv University and Google, Tel Aviv, Israel

3. Google, Tel Aviv, Israel

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.

Funder

Israel Science Foundation

Blavatnik family foundation

European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Hardware and Architecture,Information Systems,Control and Systems Engineering,Software

Reference46 articles.

1. A framework for adversarial streaming via differential privacy and difference estimators;Attias Idan;CoRR,2021

2. Counting Distinct Elements in a Data Stream

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