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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://mu.eprints-hosting.org/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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