The More You Know: Improving Laser Fault Injection with Prior Knowledge

Marina Krcek, Thomas Ordas, Daniele Fronte, Stjepan Picek

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


We consider finding as many faults as possible on the target device in the laser fault injection security evaluation. Since the search space is large, we require efficient search methods. Recently, an evolutionary approach using a memetic algorithm was proposed and shown to find more interesting parameter combinations than random search, which is commonly used. Unfortunately, once a variation on the bench or target is introduced, the process must be repeated to find suitable parameter combinations anew.To negate the effect of variation, we propose a novel method combining a memetic algorithm with a machine learning approach called a decision tree. Our approach improves the memetic algorithm by using prior knowledge of the target introduced in the initial phase of the memetic algorithm. In our experiments, the decision tree rules enhance the performance of the memetic algorithm by finding more interesting faults in different samples of the same target. Our approach shows more than two orders of magnitude better performance than random search and up to 60% better performance than previous state-of-the-art results with a memetic algorithm. Another advantage of our approach is human-readable rules, allowing the first insights into the explainability of target characterization for laser fault injection.
Original languageEnglish
Title of host publicationProceedings of the 2022 Workshop on Fault Detection and Tolerance in Cryptography (FDTC)
EditorsL. Trinh
Place of PublicationPiscataway
Number of pages12
ISBN (Electronic)978-1-6654-5442-1
ISBN (Print)978-1-6654-5443-8
Publication statusPublished - 2022
Event2022 Workshop on Fault Detection and Tolerance in Cryptography (FDTC) - , Italy
Duration: 16 Sep 202216 Sep 2022


Workshop2022 Workshop on Fault Detection and Tolerance in Cryptography (FDTC)

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Laser Fault Injection
  • Decision Tree
  • Transferability


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