Private Browser Fingerprinting
This repository contains the source code and datasets used in the Machine Learning in Networking (MaLeNe) Workshop paper Browser Fingerprinting: How to Protect Machine Learning Models and Data with Differential Privacy?.
The code directory contains the source code for non-private browser fingerprinting and plots of our evaluation.
The data directory contains the dataset used in the paper.
The privacy-code directory contains the code for private browser fingerprinting, the synthetic datasets, and Fletcher and Islam's implementation of a Differentially Private Random Decision Forest (privacy-code/DP_Random_Forest/ - licensed under GPLv3).
License Information
As stated in the LICENSE file, we release everything under GPLv3 or any later version. For information about the licenses of the used third-party packages and repositories, please refer to the LICENSES-THIRD-PARTIES file.