An interactive mechanism is an algorithm that stores a data set and answers adaptively chosen queries to it. The mechanism is called differentially private, if any adversary cannot distinguish whether a specific individual is in the data set by interacting with the mechanism. We study composition properties of differential privacy in concurrent compositions. In this setting, an adversary interacts with k interactive mechanisms in parallel and can interleave its queries to the mechanisms arbitrarily. Previously, Vadhan and Wang [2021] proved an optimal concurrent composition theorem for pure-differential privacy. We significantly generalize and extend their results. Namely, we prove optimal parallel composition properties for several major notions of differential privacy in the literature, including approximate DP, R\'enyi DP, and zero-concentrated DP. Our results demonstrate that the adversary gains no advantage by interleaving its queries to independently running mechanisms. Hence, interactivity is a feature that differential privacy grants us for free. Concurrently and independently of our work, Vadhan and Zhang [2022] proved an optimal concurrent composition theorem for f-DP [Dong et al., 2022], which implies our result for the approximate DP case.
翻译:互动机制是一种包含数据集并回答自定选择的询问的算法。 如果任何对手无法通过与机制互动来区分某个特定个人是否在数据集中,这个机制被称为有差异的私人机制。 我们研究不同隐私在同时构成中的构成特性。 在这种环境下,对手与 k 互动机制平行互动,可以任意将其询问与机制联系起来。 以前, Vadhan 和 Wang [2021年] 被证明是一种最佳的同步构成, 用于纯粹的隐私。 我们大大地概括和扩展了它们的结果。 也就是说, 我们证明, 包括接近DP、 R\'enyi DP 和零集中化DP在内的文献中若干主要隐私概念的最佳平行构成特征。 我们的结果表明, 敌对者没有通过对独立运行机制的询问而获得优势。 因此, 互动性是一个差异性特征,可以使我们免费获得隐私。 同时, 与我们的工作无关, Vadhan 和Zhang [2022年] 被证明是f-DP [Dong et al, 2022] 的最佳同时构成最佳的特征, 这意味着我们接近DP 的情况的结果。