Datatset: Machine-Learning Side-Channel Attacks on the GALACTICS Constant-Time Implementation of BLISS
Soundes Marzougui, Nils Wisiol, Patrick Gersch, Juliane Krämer, Jean‐Pierre Seifert · Zenodo (CERN European Organization for Nuclear Research) · 2021
This dataset accompanies the paper "Machine-Learning Side-Channel Attacks on the GALACTICS Constant-Time Implementation of BLISS". It was used to experimentally prove the presented attack strategies on real hardware. The corresponding source code for all three attacks is also publicly available. A detailed description of how the data was obtained can be found in the paper. Section 4 precisely describes the experimental setup. Prerequisites: sudo apt-get install p7zip Extract the data: 7z x galactics_attack_data.7z Running the attacks: The source code to run the three presented attacks can be found on Github. The instructions on how to use the python code can be obtained from the corresponding README. Re-using the dataset: The dataset consists of .pickle and .bin files. The .pickle files can be read using Pythons Pandas library. Python access functions for the .bin files are also provided.