Avoiding Floating-Point Side Channels in the Report Noisy Max with Gap Mechanism

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Zeyu Ding
https://orcid.org/0000-0003-1132-7079
John Durrell
Daniel Kifer
Prottay Protivash
Guanhong Wang
Yuxin Wang
Yingtai Xiao
Danfeng Zhang

Abstract

The Noisy Max mechanism and its variations are fundamental private selection algorithms that are used to select items from a set of candidates (such as the most common diseases in a population), while controlling the privacy leakage in the underlying data. A recently proposed extension, Noisy Top-k with Gap, provides numerical information about how much better the selected items are compared to the non-selected items (e.g., how much more common are the selected diseases). This extra information comes at no privacy cost but crucially relies on infinite precision for the privacy guarantees. In this paper, we provide a finite-precision secure implementation of this algorithm that takes advantage of integer arithmetic.

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How to Cite
Ding, Zeyu, John Durrell, Daniel Kifer, Prottay Protivash, Guanhong Wang, Yuxin Wang, Yingtai Xiao, and Danfeng Zhang. 2025. “Avoiding Floating-Point Side Channels in the Report Noisy Max With Gap Mechanism”. Journal of Privacy and Confidentiality 15 (3). https://doi.org/10.29012/jpc.894.
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