Synthetic Data Generation Framework (SGF)
Files: 2.31 MB
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.
- 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.