Deep Learning for Computational Problems in Hardware Security Modeling Attacks on Strong Physically Unclonable Function Circuits /
The book discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promi...
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| 主要な著者: | Santikellur, Pranesh (著者), Chakraborty, Rajat Subhra (著者) |
|---|---|
| 団体著者: | SpringerLink (Online service) |
| フォーマット: | 電子媒体 eBook |
| 言語: | 英語 |
| 出版事項: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
|
| 版: | 1st ed. 2023. |
| シリーズ: | Studies in Computational Intelligence,
1052 |
| 主題: | |
| オンライン・アクセス: | https://doi.org/10.1007/978-981-19-4017-0 |
| タグ: |
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