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...
-д хадгалсан:
| Үндсэн зохиолчид: | , |
|---|---|
| Байгууллагын зохиогч: | |
| Формат: | Цахим Цахим ном |
| Хэл сонгох: | англи |
| Хэвлэсэн: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
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| Хэвлэл: | 1st ed. 2023. |
| Цуврал: | Studies in Computational Intelligence,
1052 |
| Нөхцлүүд: | |
| Онлайн хандалт: | https://doi.org/10.1007/978-981-19-4017-0 |
| Шошгууд: |
Шошго нэмэх
Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!
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Агуулга:
- Chapter 1: Introduction
- Chapter 2: Fundamental Concepts of Machine Learning
- Chapter 3: Supervised Machine Learning Algorithms for PUF Modeling Attacks
- Chapter 4: Deep Learning based PUF Modeling Attacks
- Chapter 5: Tensor Regression based PUF Modeling Attack
- Chapter 6: Binarized Neural Network based PUF Modeling
- Chapter 7: Conclusions and Future Work. .