2021/11/26 by Haim Kaplan, Uri Stemmer, Kaplan, Haim +1
Computer Science · #Cryptography and Data Security #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Mobile Crowdsensing and Crowdsourcing #Privacy-Preserving Technologies in Data
paper · pdf · doi:10.48550/arxiv.2111.13762
openalex publication_date 2021/11/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.