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Deep Learning for Computational Problems in Hardware Security
- Modeling Attacks on Strong Physically Unclonable Function Circuits
Af: Pranesh Santikellur, Rajat Subhra Chakraborty
Engelsk Hardback
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Deep Learning for Computational Problems in Hardware Security
- Modeling Attacks on Strong Physically Unclonable Function Circuits
Af: Pranesh Santikellur, Rajat Subhra Chakraborty
Engelsk Hardback
Hardback
907 kr
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6 - 8 hverdage
Om denne bog
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 promising hardware security primitives. The volume is self-contained and includes a comprehensive background on PUF circuits, and the necessary mathematical foundation of traditional and advanced machine learning techniques such as support vector machines, logistic regression, neural networks, and deep learning. This book can be used as a self-learning resource for researchers and practitioners of hardware security, and will also be suitable for graduate-level courses on hardware security and application of machine learning in hardware security. A stand-out feature of the book is the availability of reference software code and datasets to replicate the experiments described in the book.
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Product detaljer
Sprog:
Engelsk
Sider:
84
ISBN-13:
9789811940163
Indbinding:
Hardback
Udgave:
ISBN-10:
9811940169
Kategori:
Udg. Dato:
16 sep 2022
Længde:
12mm
Bredde:
242mm
Højde:
163mm
Forlag:
Springer Verlag, Singapore
Oplagsdato:
16 sep 2022
Forfatter(e):
Kategori sammenhænge