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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
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=diffpriv to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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