- Thesis:
- Bachelor in Mathematics
- Author:
- Felix Maximilian Schürzinger
- Title:
- A statistical framework for differential privacy
- Supervisor:
- Jan JOHANNES
- Abstract:
- A goal of statistical privacy is to construct a data release mechanism that protects individual privacy while preserving information content. Differential privacy is a privacy requirement developed by computer scientists. We consider differential privacy from a statistical perspective and study several data-release mechanisms that satisfy differential privacy. We compare these schemes by computing the rate of convergence of distributions and densities constructed from the released data.
- References:
- L. Wasserman and S. Zhou. A statistical framework for differential privacy, Journal of the American Statistical Association, 105(489):375–389, 2010.
| Statistics Group | Institute for Mathematics | Faculty of Mathematics and Computer Science | University Heidelberg |