Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6871850 | Discrete Applied Mathematics | 2016 | 13 Pages |
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.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Naoise Holohan, Douglas J. Leith, Oliver Mason,