brubinstein/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

Maintainer
LicenseMIT + file LICENSE
Version0.4.2.9000
URL https://github.com/brubinstein/diffpriv http://brubinstein.github.io/diffpriv
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("brubinstein/diffpriv")
brubinstein/diffpriv documentation built on July 7, 2022, 4:23 a.m.