May 14, 2024, 4:11 a.m. | Soner Aydin, Sinan Yildirim

cs.CR updates on

arXiv:2405.07020v1 Announce Type: cross
Abstract: We propose a novel Bayesian approach for the adaptive and online estimation of the frequency distribution of a finite number of categories under the local differential privacy (LDP) framework. The proposed algorithm performs Bayesian parameter estimation via posterior sampling and adapts the randomization mechanism for LDP based on the obtained posterior samples. We propose a randomized mechanism for LDP which uses a subset of categories as an input and whose performance depends on the selected …

algorithm arxiv cs.lg differential privacy distribution distributions framework local mechanism novel parameter privacy randomization under

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