Cryptology ePrint Archive: Report 2019/866

A Fast Characterization Method for Semi-invasive Fault Injection Attacks

Lichao Wu and Gerard Ribera and Noemie Beringuier-Boher and Stjepan Picek

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 on characterizing 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.

Category / Keywords: implementation / Physical attacks, Fault injection, Fast space characterization, Deep learning, Metrics

Date: received 24 Jul 2019, last revised 21 Sep 2019

Contact author: picek stjepan at gmail com,L Wu-4@tudelft nl,gerard ribera s@gmail com,nowe 66@gmail com

Available format(s): PDF | BibTeX Citation

Version: 20190921:214106 (All versions of this report)

Short URL: ia.cr/2019/866


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