README.md

A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data

This repository contains the source code for the paper A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data by M.S.M.S. Annamalai, A. Gadotti, L. Rocher, presented August 2024 at USENIX Security 2024 link.

Install

Dependencies are managed by mamba/conda. The required dependencies can be installed using the command [conda/mamba] env create -f env.yml and then run [conda/mamba] activate recon_synth.

A license to Gurobi is also necessary to run the code, which for academics can be gotten for free here. The license can be subsequently installed using the command grbgetkey <KEY>.

Usage

The entire experiment pipeline to generate the results we used for the paper can be run using the following series of commands. Please note that you can change the REPS, N_PROCS, and DATA_DIR variables in these scripts to change the number of repetitions of the privacy game, number of processors to use during parallelization, and the output directory of the results respectively.

$ cd priv_game
$ scripts/prep_exps.sh
$ scripts/run_exps.sh
$ scripts/prep_extra_exps.sh
$ scripts/run_extra_exps.sh
$ scripts/time_attack.sh
$ scripts/log_memory.sh

After running all the experiments, results can be visualized using the plot_results.ipynb notebook.

Available SDG Models

Here is a table of available SDG models and their descriptions.

SDG Model	Description
NonPrivate	Sample directly from target dataset with replacement
CTGAN	Generative adversarial network from MIT SDV library
IndHist	Independently sample attributes from 1D histogram
BayNet_3parents	Bayesian network (with hyperparameter: 3 parents)
PrivBayes_3parents_1eps	PrivBayes model (with hyperparameters: 3 parents, $\varepsilon = 1$)
RAP_2Kiters	Relaxed Adaptive Projection algorithm (with hyperparameter: 2000 iterations)
RAP_2Kiters_1eps	RAP algorithm (with hyperparameters: 2000 iterations, $\varepsilon = 1$)

Available Datasets

We provide 2 datasets in this repo acs and fire.

Acknowledgements

Code in the generative_models/rap_src folder is cloned and slightly modified (to suit our import system) from dp-query-release.