On Linear Time Decidability of Differential Privacy for Programs with Unbounded Inputs

Rohit Chadha, A. Sistla, Mahesh Viswanathan
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引用次数: 2

Abstract

We introduce an automata model for describing interesting classes of differential privacy mechanisms/algorithms that include known mechanisms from the literature. These automata can model algorithms whose inputs can be an unbounded sequence of real-valued query answers. We consider the problem of checking whether there exists a constant d such that the algorithm described by these automata are dϵ-differentially private for all positive values of the privacy budget parameter ϵ. We show that this problem can be decided in time linear in the automaton’s size by identifying a necessary and sufficient condition on the underlying graph of the automaton. This paper’s results are the first decidability results known for algorithms with an unbounded number of query answers taking values from the set of reals.
输入无界规划微分隐私的线性时间可判定性
我们引入了一个自动机模型来描述有趣的微分隐私机制/算法类,其中包括文献中已知的机制。这些自动机可以为输入可以是实值查询答案的无界序列的算法建模。我们考虑的问题是检查是否存在一个常数d,使得这些自动机所描述的算法对于隐私预算参数λ的所有正值都是dϵ-differentially私有的。我们通过在自动机的底层图上确定一个充要条件,证明了这个问题可以在自动机的大小上确定为时间线性的。本文的结果是已知的第一个具有无界查询答案从实数集合中取值的算法的可决性结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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