Adversarially Robust Streaming Algorithms via Differential Privacy

04/13/2020
by   Avinatan Hassidim, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/30/2021

A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators

Streaming algorithms are algorithms for processing large data streams, u...
research
11/16/2021

Improved Pan-Private Stream Density Estimation

Differential privacy is a rigorous definition for privacy that guarantee...
research
11/26/2021

A Note on Sanitizing Streams with Differential Privacy

The literature on data sanitization aims to design algorithms that take ...
research
09/08/2021

Adversarially Robust Streaming via Dense–Sparse Trade-offs

A streaming algorithm is adversarially robust if it is guaranteed to per...
research
06/28/2021

Adversarial Robustness of Streaming Algorithms through Importance Sampling

In this paper, we introduce adversarially robust streaming algorithms fo...
research
01/22/2023

Relaxed Models for Adversarial Streaming: The Advice Model and the Bounded Interruptions Model

Streaming algorithms are typically analyzed in the oblivious setting, wh...
research
06/19/2019

A unified view on differential privacy and robustness to adversarial examples

This short note highlights some links between two lines of research with...

Please sign up or login with your details

Forgot password? Click here to reset