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 |
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Author | Benjamin Rubinstein [aut, cre], Francesco Aldà [aut] |
Maintainer | Benjamin Rubinstein <brubinstein@unimelb.edu.au> |
License | MIT + file LICENSE |
Version | 0.4.2 |
URL | https://github.com/brubinstein/diffpriv http://brubinstein.github.io/diffpriv |
Package repository | View on CRAN |
Installation |
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