Differentially Private Response Mechanisms on Categorical Data

May 27, 2015 ยท The Ethereal ยท ๐Ÿ› Discrete Applied Mathematics

๐Ÿ”ฎ THE ETHEREAL: The Ethereal
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Authors Naoise Holohan, Doug Leith, Oliver Mason arXiv ID 1505.07254 Category cs.DM: Discrete Mathematics Cross-listed cs.CR, math.CO Citations 3 Venue Discrete Applied Mathematics Last Checked 2 months ago
Abstract
We study mechanisms for differential privacy on finite datasets. By deriving \emph{sufficient sets} for differential privacy we obtain necessary and sufficient conditions for differential privacy, a tight lower bound on the maximal expected error of a discrete mechanism and a characterisation of the optimal mechanism which minimises the maximal expected error within the class of mechanisms considered.
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