Print Email Facebook Twitter A Survey on Machine Learning in Hardware Security Title A Survey on Machine Learning in Hardware Security Author Köylü, T.C. (TU Delft Computer Engineering) Reinbrecht, Cezar Gebregiorgis, A.B. (TU Delft Computer Engineering) Hamdioui, S. (TU Delft Quantum & Computer Engineering) Taouil, M. (TU Delft Computer Engineering) Department Quantum & Computer Engineering Date 2023 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. To reference this document use: http://resolver.tudelft.nl/uuid:56f0d7c4-3c27-48e8-9896-a355f440986b DOI https://doi.org/10.1145/3589506 ISSN 1550-4832 Source ACM Journal on Emerging Technologies in Computing Systems, 19 (2) Part of collection Institutional Repository Document type journal article Rights © 2023 T.C. Köylü, Cezar Reinbrecht, A.B. Gebregiorgis, S. Hamdioui, M. Taouil Files PDF final_version.pdf 1.19 MB Close viewer /islandora/object/uuid:56f0d7c4-3c27-48e8-9896-a355f440986b/datastream/OBJ/view