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Erschienen in:
2023 | OriginalPaper | Buchkapitel
1. Introduction to Machine Learning for Hardware Security
verfasst von : Pranesh Santikellur, Rajat Subhra Chakraborty
Erschienen in: Deep Learning for Computational Problems in Hardware Security
Verlag: Springer Nature Singapore
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Abstract
Computing devices have become the basis of our modern lives, and hardware has long been considered as the backbone of trust for all computing systems. Various software attacks and defense mechanisms, mainly based on cryptographic measures, have been widely analyzed and applied in a variety of applications. In comparison to software security, hardware security as a topic is relatively new, and its importance has drastically increased in recent years due to the multiple attacks on hardware that were thought to be immune to attack. Hardware security is no different than any other field of security that focuses on launching attacks to steal assets and on strategies designed to protect them. In particular, the topic of hardware security is focused on situations where the assets are hardware components that contain secrets of electronic components, such as cryptographic keys and other sensitive information [1].