Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters
Samuel Haney, Michael Shoemate, Grace Tian, Salil P. Vadhan, Andrew Vyrros, Vicki Xu, Wanrong Zhang
摘要
In this paper, we study the concurrent composition of interactive mechanisms with adaptively chosen privacy-loss parameters. In this setting, the adversary can interleave queries to existing interactive mechanisms, as well as create new ones. We prove that every valid privacy filter and odometer for noninteractive mechanisms extends to the concurrent composition of interactive mechanisms if privacy loss is measured using (ϵ, δ)-DP, f -DP, or Rényi DP of fixed order. Our results offer strong theoretical foundations for enabling full adaptivity in composing differentially private interactive mechanisms, showing that concurrency does not affect the privacy guarantees. We also provide an implementation for users to deploy in practice.
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引用它的顶会 Paper4
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- DPolicy: Managing Privacy Risks Across Multiple Releases with Differential PrivacyNicolas Küchler, Alexander Viand, Hidde Lycklama, Anwar HithnawiS&P 2025
它引用的顶会 Paper3
- Fully-Adaptive Composition in Differential PrivacyJustin Whitehouse, Aaditya Ramdas, Ryan Rogers, Steven WuICML 2023 · 被引用 56 次
- Composition Theorems for Interactive Differential PrivacyXin LyuNeurIPS 2022 · 被引用 29 次
- Concurrent Composition Theorems for Differential PrivacySalil P. Vadhan, Wanrong ZhangSTOC 2023 · 被引用 11 次
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