Genetic Algorithm-Based Electromagnetic Fault Injection

Antun Maldini, Niels Samwel, Stjepan Picek, Lejla Batina

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

6 Citations (Scopus)


Electromagnetic fault injection (EMFI) is a powerful active attack, requiring minimal modifications of the device under attack while having excellent penetration capabilities. The number of possible parameter combinations when characterizing an attack is usually huge, rendering exhaustive search impossible. In this work we present a novel evolutionary algorithm for optimizing the parameters for EM fault injection, which out-performs previous search methods for EMFI. The cryptographic device under attack is treated as a black box, with only a few very general assumptions on its inner workings. We test our evolutionary algorithm by attacking SHA-3 where we are able to obtain 40 times more faulty measurements and 20 times more distinct fault measurements than the random search. When coupled with the algebraic fault attack, we get 25% more exploitable faults per individual measurement.

Original languageEnglish
Title of host publication2018 Workshop on Fault Diagnosis and Tolerance in Cryptography FDTC
Subtitle of host publicationProceedings
EditorsJ.E. Guerrero
Place of PublicationPiscataway, NJ
Number of pages8
ISBN (Electronic)978-1-5386-8197-8
ISBN (Print)978-1-5386-8198-5
Publication statusPublished - 2018
Event15th Workshop on Fault Diagnosis and Tolerance in Cryptography, FDTC 2018 - Amsterdam, Netherlands
Duration: 13 Sep 201813 Sep 2018


Conference15th Workshop on Fault Diagnosis and Tolerance in Cryptography, FDTC 2018


  • Algebraic Fault Attack
  • Electromagnetic Fault Injection
  • Genetic Algorithm
  • Local Search
  • Parameter Optimization
  • SHA-3


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