Synthetic Data Generation Framework (SGF)

The Synthetic Data Generation Framework (SGF) is a software tool that can quickly produce synthetic datasets in a privacy-preserving way. It is written in C++ and is easy to extend. Given a sensitive dataset as input, the tool is able to produce a collection synthetic data records in a way that provably guarantees differential privacy.

Limitations:

• Currently only input datasets with categorical and discrete attributes are supported.

The archive file (tar.gz) contains the (C++) source code alongside with a README file and example data.