A Survey on Machine Learning in Hardware Security

T.C. Köylü, Cezar Reinbrecht, A.B. Gebregiorgis, S. Hamdioui, M. Taouil

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Hardware security is currently a very influential domain, where each year countless works are published concerning attacks against hardware and countermeasures. A significant number of them use machine learning, which is proven to be very effective in other domains. This survey, as one of the early attempts, presents the usage of machine learning in hardware security in a full and organized manner. Our contributions include classification and introduction to the relevant fields of machine learning, a comprehensive and critical overview of machine learning usage in hardware security, and an investigation of the hardware attacks against machine learning (neural network) implementations.
Original languageEnglish
Article number18
Number of pages37
JournalACM Journal on Emerging Technologies in Computing Systems
Volume19
Issue number2
DOIs
Publication statusPublished - 2023

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