Articoli correlati a Deep Learning for Computational Problems in Hardware...

Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits: 1052 - Brossura

 
9789811940194: Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits: 1052

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

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.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

EUR 10,42 per la spedizione da Regno Unito a Italia

Destinazione, tempi e costi

Altre edizioni note dello stesso titolo

9789811940163: Deep Learning for Computational Problems in Hardware Security: Modeling Attacks on Strong Physically Unclonable Function Circuits: 1052

Edizione in evidenza

ISBN 10:  9811940169 ISBN 13:  9789811940163
Casa editrice: Springer Nature, 2022
Rilegato

Risultati della ricerca per Deep Learning for Computational Problems in Hardware...

Foto dell'editore

Santikellur, Pranesh; Chakraborty, Rajat Subhra
Editore: Springer, 2023
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Brossura

Da: Ria Christie Collections, Uxbridge, Regno Unito

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. In. Codice articolo ria9789811940194_new

Contatta il venditore

Compra nuovo

EUR 60,65
Convertire valuta
Spese di spedizione: EUR 10,42
Da: Regno Unito a: Italia
Destinazione, tempi e costi

Quantità: Più di 20 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Santikellur, Pranesh|Chakraborty, Rajat Subhra
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Brossura
Print on Demand

Da: moluna, Greven, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: 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. Codice articolo 1071298104

Contatta il venditore

Compra nuovo

EUR 92,27
Convertire valuta
Spese di spedizione: EUR 9,70
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: Più di 20 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Rajat Subhra Chakraborty
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Taschenbuch
Print on Demand

Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: 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. Codice articolo 9789811940194

Contatta il venditore

Compra nuovo

EUR 106,99
Convertire valuta
Spese di spedizione: EUR 11,00
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Rajat Subhra Chakraborty
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Taschenbuch

Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: 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. Codice articolo 9789811940194

Contatta il venditore

Compra nuovo

EUR 106,99
Convertire valuta
Spese di spedizione: EUR 15,00
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Rajat Subhra Chakraborty
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Taschenbuch

Da: AHA-BUCH GmbH, Einbeck, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: 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. Codice articolo 9789811940194

Contatta il venditore

Compra nuovo

EUR 109,94
Convertire valuta
Spese di spedizione: EUR 14,99
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 1 disponibili

Aggiungi al carrello

Foto dell'editore

Santikellur, Pranesh/ Chakraborty, Rajat Subhra
Editore: Springer Nature, 2023
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Paperback

Da: Revaluation Books, Exeter, Regno Unito

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Paperback. Condizione: Brand New. 97 pages. 9.25x6.10x0.21 inches. In Stock. Codice articolo x-9811940193

Contatta il venditore

Compra nuovo

EUR 147,20
Convertire valuta
Spese di spedizione: EUR 11,59
Da: Regno Unito a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Foto dell'editore

Santikellur, Pranesh; Chakraborty, Rajat Subhra
Editore: Springer, 2023
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Brossura
Print on Demand

Da: Majestic Books, Hounslow, Regno Unito

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. Print on Demand pp. 100. Codice articolo 397857052

Contatta il venditore

Compra nuovo

EUR 151,93
Convertire valuta
Spese di spedizione: EUR 10,25
Da: Regno Unito a: Italia
Destinazione, tempi e costi

Quantità: 4 disponibili

Aggiungi al carrello

Foto dell'editore

Santikellur, Pranesh; Chakraborty, Rajat Subhra
Editore: Springer, 2023
ISBN 10: 9811940193 ISBN 13: 9789811940194
Nuovo Brossura
Print on Demand

Da: Biblios, Frankfurt am main, HESSE, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Condizione: New. PRINT ON DEMAND pp. 100. Codice articolo 18398552777

Contatta il venditore

Compra nuovo

EUR 159,58
Convertire valuta
Spese di spedizione: EUR 7,95
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 4 disponibili

Aggiungi al carrello