This repository contains the source code for the paper Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple’s Count Mean Sketch in Practice by A. Gadotti, F. Houssiau, M.S.M.S. Annamalai, Y.-A. de Montjoye, presented August 2022 at USENIX Security 2022 [link].

Please make sure that conda is installed. After that, the dependencies for this project can be installed by running the following command:

$ conda env create --file conda_deps.yml

Additionally, if you would like to achieve the same plot styles, make sure that LaTeX and the LinLibertine font is installed.

All the experiments are given in the experiments.ipynb notebook which can be run individually. Each function has been annotated with a docstring for further use and modification.

Please note that the Twitter dataset used in the paper cannot be redistributed by us and therefore it is not included in this repository.

GNU General Public License v3.0