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.

Package details

AuthorBenjamin Rubinstein [aut, cre], Francesco Aldà [aut]
MaintainerBenjamin Rubinstein <[email protected]>
LicenseMIT + file LICENSE
URL https://github.com/brubinstein/diffpriv http://brubinstein.github.io/diffpriv
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the diffpriv package in your browser

Any scripts or data that you put into this service are public.

diffpriv documentation built on July 18, 2017, 5:02 p.m.