Article ID Journal Published Year Pages File Type
6871850 Discrete Applied Mathematics 2016 13 Pages PDF
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.
Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
Authors
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