84 citations · 214 across the 16 of their papers we have counts for
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cs.CR2022★ 8 cited
Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy
Skye Berghel, Philip Bohannon, Damien Desfontaines +10
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 Found…
cs.CR2022★ 7 cited
Precision-based attacks and interval refining: how to break, then fix, differential privacy on finite computers
Samuel Haney, Damien Desfontaines, Luke Hartman +2
Despite being raised as a problem over ten years ago, the imprecision of floating point arithmetic continues to cause privacy failures in the implementations of differentially priv…