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arXiv · 2111.13762

A Note on Sanitizing Streams with Differential Privacy

Haim Kaplan·Uri Stemmer
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Abstract

The literature on data sanitization aims to design algorithms that take an input dataset and produce a privacy-preserving version of it, that captures some of its statistical properties. In this note we study this question from a streaming perspective and our goal is to sanitize a data stream. Specifically, we consider low-memory algorithms that operate on a data stream and produce an alternative privacy-preserving stream that captures some statistical properties of the original input stream.

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Haim Kaplan, Uri Stemmer. 2021-11-26. A Note on Sanitizing Streams with Differential Privacy. https://arxiv.org/abs/2111.13762

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