diffpriv: Easy Differential Privacy
Version 0.4.2

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) . Example mechanisms include the Laplace mechanism for releasing numeric aggregates, and the exponential mechanism for releasing set elements. A sensitivity sampler (Rubinstein & Alda, 2017) 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]
Date of publication2017-07-18 11:42:21 UTC
MaintainerBenjamin Rubinstein <[email protected]>
LicenseMIT + file LICENSE
URL https://github.com/brubinstein/diffpriv http://brubinstein.github.io/diffpriv
Package repositoryView on CRAN
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diffpriv documentation built on July 18, 2017, 5:02 p.m.