Private Federated Statistics in an Interactive Setting

2022/11/18 by Audra McMillan, Omid Javidbakht, McMillan, Audra +45 · 1 citation
Computer Science · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Internet Traffic Analysis and Secure E-voting #Mobile Crowdsensing and Crowdsourcing #Privacy-Preserving Technologies in Data

paper · pdf · doi:10.48550/arxiv.2211.10082

openalex publication_date 2022/11/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Privately learning statistics of events on devices can enable improved user experience. Differentially private algorithms for such problems can benefit significantly from interactivity. We argue that an aggregation protocol can enable an interactive private federated statistics system where user's devices maintain control of the privacy assurance. We describe the architecture of such a system, and analyze its security properties.

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