Optimum Noise Mechanism for Differentially Private Queries in Discrete Finite Sets

arXiv:2111.11661v3 Announce Type: replace
Abstract: The Differential Privacy (DP) literature often centers on meeting privacy constraints by introducing noise to the query, typically using a pre-specified parametric distribution model with one or two degrees of freedom. However, this emphasis tends to neglect the crucial considerations of response accuracy and utility, especially in the context of categorical or discrete numerical database queries, where the parameters defining the noise distribution are finite and could be chosen optimally. This paper addresses this gap …

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