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Barnes and Noble

Deep Learning for Computational Problems Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits

Current price: $109.99
Deep Learning for Computational Problems Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits
Deep Learning for Computational Problems Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits

Barnes and Noble

Deep Learning for Computational Problems Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits

Current price: $109.99
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Size: Hardcover

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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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Barnes & Noble does business -- big business -- by the book. As the #1 bookseller in the US, it operates about 720 Barnes & Noble superstores (selling books, music, movies, and gifts) throughout all 50 US states and Washington, DC. The stores are typically 10,000 to 60,000 sq. ft. and stock between 60,000 and 200,000 book titles. Many of its locations contain Starbucks cafes, as well as music departments that carry more than 30,000 titles.

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