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Journal of Electronic Testing
Erschienen in: Journal of Electronic Testing 2/2018

18.04.2018

Machine Learning for Hardware Security: Opportunities and Risks

verfasst von: Rana Elnaggar, Krishnendu Chakrabarty

Erschienen in: Journal of Electronic Testing | Ausgabe 2/2018

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Abstract

Recently, machine learning algorithms have been utilized by system defenders and attackers to secure and attack hardware, respectively. In this work, we investigate the impact of machine learning on hardware security. We explore the defense and attack mechanisms for hardware that are based on machine learning. Moreover, we identify suitable machine learning algorithms for each category of hardware security problems. Finally, we highlight some important aspects related to the application of machine learning to hardware security problems and show how the practice of applying machine learning to hardware security problems has changed over the past decade.
Vorheriger Artikel Application of Machine Learning Techniques in Post-Silicon Debugging and Bug Localization
Nächster Artikel Measurement of Nonlinear Dielectric Behaviour of Semiconductor Material Under Microwave Field in Dual-Mode Rectangular Cavity

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Metadaten
Titel
Machine Learning for Hardware Security: Opportunities and Risks
verfasst von
Rana Elnaggar
Krishnendu Chakrabarty
Publikationsdatum
18.04.2018
Verlag
Springer US
Erschienen in
Journal of Electronic Testing / Ausgabe 2/2018
Print ISSN: 0923-8174
Elektronische ISSN: 1573-0727
DOI
https://doi.org/10.1007/s10836-018-5726-9

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