Exact and Efficient Bayesian Inference for Privacy Risk Quantification (Accompanying Artifact)
The artifact consists of a virtual machine with all necessary software to execute the code accompanying in the paper's GitHub repository: https://github.com/itu-square/gauss-privug. The repository contains a proof-of-concept implementation of our inference engine. All the experiments in the paper are included here. For convenience, they are presented in a Jupyter notebook with further comments. The experiments generate all the evaluation plots in the paper.
The password of the Zip file is: sefm_conference_2023