NEWS.md

In diffpriv: Easy Differential Privacy

diffpriv 0.4.2

• Second vignette bernstein on: Bernstein approximations and use of DPMechBernstein for private function release.
• Minor edits to docs

diffpriv 0.4.1

• Expanding test coverage of Bernstein mechanism and function approximation code.

diffpriv 0.4.0

• Addition of S3 constructor and predict() generic implementation for fitting (non-iterated) Bernstein polynomial function approximations.
• Addition of DPMechBernstein class implementing the Bernstein mechanism of Alda and Rubinstein (AAAI'2017), for privately releasing functions.
• Bug fix in the Laplace random sampler affecting DPMechLaplace
• Unit test coverage of new functionality; general documentation improvements.

diffpriv 0.3.2

• Addition of DPMechGaussian class for the generic Gaussian mechanism to README, Vignette. Resolves #2
• Minor test additions.

diffpriv 0.3.1

• Refactoring around releaseResponse() method in DPMechNumeric. Resolves #1
• Increased test coverage.

diffpriv 0.3.0

• New DPMechGaussian class implementing the Gaussian mechanism, which achieves (epsilon,delta)-differential privacy by adding Gaussian noise to numeric responses calibrated by L2-norm sensitivity.
• Refactoring of DPMechGaussian and DPMechLaplace underneath a new VIRTUAL class DPMechNumeric which contains common methods, dims slot (formerly dim changed because dim is a special slot for S4).

diffpriv 0.2.0

• DPMechLaplace objects can now be initialized without specifying non-private target response dim. In such cases, the sensitivity sampler will perform an additional target probe to determine dim.

diffpriv 0.1.0.901

• Sensitivity sampler methods no longer require oracles that return lists. Acceptable oracles may now return lists, matrices, data frames, numeric vectors, or char vectors. As a consequence some example code in docs, README and vignette, is simplified.

diffpriv 0.1.0.900

• Initial release

diffpriv documentation built on May 2, 2019, 2:38 a.m.