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Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis

The current repository is associated with the article "Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis" available on IACR Transactions on Cryptographic Hardware and Embedded Systems (TCHES) and the eprints.

The optimized Ranking Loss has been developed by Pritha Gupta (credit: issue 1) and validated on Tensorflow 2.0.

Each dataset is composed of the following scripts and repositories:

The trace sets were obtained from publicly databases:

Raw data files hashes

The zip file SHA-256 hash value is:


AES_HD/AES_HD_dataset.zip: 00a3d02f01bae8c4fcefda33e3d1adb57bed0509ded3cdcf586e213b3d87e41b


ASCAD/Desync0/ASCAD_dataset.zip: 5f5924e2d0beca5b57fbc48ace137dbb2fe12dd03976aa38f4a699ab21e966b0

ASCAD/Desync50/ASCAD_dataset.zip: 9bf704727390a73cf67d3952bc2cacef532b0b62e55f85d615edaa6cd8521f51

ASCAD/Desync100/ASCAD_dataset.zip: 2d803db27e58fec3d805cd3cf039b303cad1e0c9ea7a8102a07020bd07113cd9


Citation

If you use our code, models or wish to refer to our results, please use the following BibTex entry:

@article{Zaid_Bossuet_Dassance_Habrard_Venelli_2020, 
title={Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis}, 
volume={2021}, 
url={https://tches.iacr.org/index.php/TCHES/article/view/8726}, 
DOI={10.46586/tches.v2021.i1.25-55}, 
number={1}, 
journal={IACR Transactions on Cryptographic Hardware and Embedded Systems}, 
author={Zaid, Gabriel and Bossuet, Lilian and Dassance, François and Habrard, Amaury and Venelli, Alexandre}, 
year={2020}, 
month={Dec.}, 
pages={25-55} 
}

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