diffpriv
Easy Differential Privacy
An implementation of major general-purpose mechanisms for privatizing statistics, models, and machine learners, within the framework of differential privacy of Dwork et al. (2006) <doi:10.1007/11681878_14>. Example mechanisms include the Laplace mechanism for releasing numeric aggregates, and the exponential mechanism for releasing set elements. A sensitivity sampler (Rubinstein & Alda, 2017) <arXiv:1706.02562> permits sampling target non-private function sensitivity; combined with the generic mechanisms, it permits turn-key privatization of arbitrary programs.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.4.2 |
2026-04-09 windows/windows R-4.5 | diffpriv_0.4.2.zip |
713.2 KiB |