Articles liés à Deep Learning for Computational Problems in Hardware...
Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits - Couverture souple
Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Pranesh Santikellur is a Ph.D. student and a Senior Research Fellow in the Department of Computer Science and Engineering at the Indian Institute of Technology, Kharagpur. He received his B.E. degree in Electronics & Communication Engineering from Visvesvaraya Technological University, Belgaum, India, in 2010. He has a total of 6 years of industry experience at Horner Engineering India Pvt. Ltd. and Processor Systems. His primary research interest lies in hardware security, deep learning, and programmable logic controller security. He is an IEEE student member.
Rajat Subhra Chakraborty is an Associate Professor in the Department of Computer Science & Engineering of the Indian Institute of Technology, Kharagpur, India. He has professional experience working in National Semiconductor and Advanced Micro Devices (AMD). His research interest lies in the areas of hardware security, VLSI design, digital watermarking, and digital image forensics, in which he has published 4 books and over 100 papers in international journals and conferences of repute. He holds 2 granted U.S. patents. His publications have received over 3600 citations to date. Dr. Chakraborty has a Ph.D. in Computer Engineering from Case Western Reserve University, USA, and is a senior member of IEEE and ACM.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 60,67
EUR 4,62 expédition depuis Royaume-Uni vers France
Destinations, frais et délaisAutres éditions populaires du même titre
Résultats de recherche pour Deep Learning for Computational Problems in Hardware...
Image d'archives
Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits (Studies in Computational Intelligence)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9789811940194_new
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Deep Learning for Computational Problems in Hardware Security
Edité par
Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10 : 9811940193
ISBN 13 : 9789811940194
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 Functio. N° de réf. du vendeur 1071298104
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Deep Learning for Computational Problems in Hardware Security
Edité par
Springer Nature Singapore Sep 2023, 2023
ISBN 10 : 9811940193
ISBN 13 : 9789811940194
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 100 pp. Englisch. N° de réf. du vendeur 9789811940194
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Deep Learning for Computational Problems in Hardware Security : Modeling Attacks on Strong Physically Unclonable Function Circuits
Edité par
Springer Nature Singapore, Springer Nature Singapore, 2023
ISBN 10 : 9811940193
ISBN 13 : 9789811940194
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9789811940194
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Deep Learning for Computational Problems in Hardware Security
Edité par
Springer Nature Singapore, Springer Nature Singapore Sep 2023, 2023
ISBN 10 : 9811940193
ISBN 13 : 9789811940194
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 100 pp. Englisch. N° de réf. du vendeur 9789811940194
Quantité disponible : 2 disponible(s)
Image d'archives
Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : Brand New. 97 pages. 9.25x6.10x0.21 inches. In Stock. N° de réf. du vendeur x-9811940193
Quantité disponible : 2 disponible(s)
Image d'archives
Deep Learning for Computational Problems in Hardwa
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Print on Demand pp. 100. N° de réf. du vendeur 397857052
Quantité disponible : 4 disponible(s)
Image d'archives
Deep Learning for Computational Problems in Hardwa
impression à la demandeVendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. PRINT ON DEMAND pp. 100. N° de réf. du vendeur 18398552777
Quantité disponible : 4 disponible(s)