Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy

2022/12/08 by Skye Berghel, Berghel, Skye, Philip Bohannon +23 · 2 citations
Computer Science · Medicine · #COVID-19 Digital Contact Tracing #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #HIV, Drug Use, Sexual Risk #Privacy-Preserving Technologies in Data

paper · pdf · doi:10.48550/arxiv.2212.04133

openalex publication_date 2022/12/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this short paper, we outline the design of Tumult Analytics, a Python framework for differential privacy used at institutions such as the U.S. Census Bureau, the Wikimedia Foundation, or the Internal Revenue Service.

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