Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.dam.2016.04.010 | Discrete Applied Mathematics |
Keywords | DocType | Volume |
Data privacy,Differential privacy,Optimal mechanisms | Journal | abs/1505.07254 |
Issue | ISSN | Citations |
C | 0166-218X | 0 |
PageRank | References | Authors |
0.34 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naoise Holohan | 1 | 3 | 1.05 |
| Douglas J. Leith | 2 | 1332 | 116.75 |
| Oliver Mason | 3 | 107 | 12.58 |