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    Differentially Private Response Mechanisms on Categorical Data


    Holohan, Naoise, Leith, Douglas J. and Mason, Oliver (2015) Differentially Private Response Mechanisms on Categorical Data. Working Paper. Arxiv.

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    Official URL: http://arxiv.org/abs/1505.07254

    Abstract

    We study mechanisms for differential privacy on finite datasets. By deriving 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.
    Item Type: Monograph (Working Paper)
    Keywords: Data Privacy; Differential Privacy; Optimal Mechanisms;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Science and Engineering > Mathematics and Statistics
    Item ID: 6232
    Identification Number: arXiv:1505.07254
    Depositing User: Oliver Mason
    Date Deposited: 03 Jul 2015 14:22
    Publisher: Arxiv
    URI: https://mural.maynoothuniversity.ie/id/eprint/6232
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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