Genetic Algorithm-Based Electromagnetic Fault Injection
| Autor: | Maldini, Antun, Samwel, N., Picek, Stjepan, Batina, L., Guerrero, J.E. |
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| Přispěvatelé: | Guerrero, J.E. |
| Rok vydání: | 2018 |
| Předmět: |
021110 strategic
defence & security studies business.industry Computer science 0211 other engineering and technologies Evolutionary algorithm Brute-force search Cryptography 02 engineering and technology Fault injection Evolutionary computation Rendering (computer graphics) Random search Genetic algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Digital Security business Algorithm |
| Zdroj: | Guerrero, J.E. (ed.), 2018 Workshop on Fault Diagnosis and Tolerance in Cryptography, FDTC 2018, Amsterdam, The Netherlands, September 13, 2018. Proceedings, pp. 35-42 Guerrero, J.E. (ed.), 2018 Workshop on Fault Diagnosis and Tolerance in Cryptography, FDTC 2018, Amsterdam, The Netherlands, September 13, 2018. Proceedings, 35-42. Piscataway : IEEE Computer Society STARTPAGE=35;ENDPAGE=42;TITLE=Guerrero, J.E. (ed.), 2018 Workshop on Fault Diagnosis and Tolerance in Cryptography, FDTC 2018, Amsterdam, The Netherlands, September 13, 2018. Proceedings FDTC |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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