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) <doi:10.48550/arXiv.1706.02562> permits sampling target non-private function sensitivity; combined with the generic mechanisms, it permits turn-key privatization of arbitrary programs.

Version:	0.4.2
Depends:	R (≥ 3.4.0)
Imports:	gsl, methods, stats
Suggests:	randomNames, testthat, knitr, rmarkdown
Published:	2017-07-18
DOI:	10.32614/CRAN.package.diffpriv
Author:	Benjamin Rubinstein [aut, cre], Francesco Aldà [aut]
Maintainer:	Benjamin Rubinstein <brubinstein at unimelb.edu.au>
BugReports:	https://github.com/brubinstein/diffpriv/issues
License:	MIT + file LICENSE
URL:	https://github.com/brubinstein/diffpriv, http://brubinstein.github.io/diffpriv
NeedsCompilation:	no
Citation:	diffpriv citation info
Materials:	README NEWS
In views:	OfficialStatistics
CRAN checks:	diffpriv results

Documentation:

Reference manual:	diffpriv.pdf
Vignettes:	bernstein diffpriv

Downloads:

Package source:	diffpriv_0.4.2.tar.gz
Windows binaries:	r-devel: diffpriv_0.4.2.zip, r-release: diffpriv_0.4.2.zip, r-oldrel: diffpriv_0.4.2.zip
macOS binaries:	r-release (arm64): diffpriv_0.4.2.tgz, r-oldrel (arm64): diffpriv_0.4.2.tgz, r-release (x86_64): diffpriv_0.4.2.tgz, r-oldrel (x86_64): diffpriv_0.4.2.tgz

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