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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 + fileLICENSE
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.html ,diffpriv.pdf
Vignettes:bernstein (source,R code)
diffpriv (source,R code)

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

Reverse dependencies:

Reverse imports:GRANDpriv

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=diffprivto link to this page.


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