@inproceedings{c43e5fee63dc4d2ba44e170356601fea,
title = "A fast characterization method for semi-invasive fault injection attacks",
abstract = "Semi-invasive fault injection attacks are powerful techniques well-known by attackers and secure embedded system designers. When performing such attacks, the selection of the fault injection parameters is of utmost importance and usually based on the experience of the attacker. Surprisingly, there exists no formal and general approach to characterize the target behavior under attack. In this work, we present a novel methodology to perform a fast characterization of the fault injection impact on a target, depending on the possible attack parameters. We experimentally show our methodology to be a successful one when targeting different algorithms such as DES and AES encryption and then extend to the full characterization with the help of deep learning. Finally, we show how the characterization results are transferable between different targets.",
keywords = "Deep learning, Fast space characterization, Fault injection, Metrics, Physical attacks",
author = "Lichao Wu and Gerard Ribera and Noemie Beringuier-Boher and Stjepan Picek",
year = "2020",
doi = "10.1007/978-3-030-40186-3_8",
language = "English",
isbn = "9783030401856",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Open",
pages = "146--170",
editor = "Stanislaw Jarecki",
booktitle = "Topics in Cryptology – CT-RSA 2020 - The Cryptographers Track at the RSA Conference 2020, Proceedings",
note = "Cryptographers Track at the RSA Conference, CT-RSA 2020 ; Conference date: 24-02-2020 Through 28-02-2020",
}