Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 69,86
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Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2022
ISBN 10: 9811940169 ISBN 13: 9789811940163
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 72,25
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Aggiungi al carrelloHardback. Condizione: New. 2023 ed. 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.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 61,52
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 61,52
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 60,92
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 67,73
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Springer Verlag, Singapore, SG, 2022
ISBN 10: 9811940169 ISBN 13: 9789811940163
Da: Rarewaves.com UK, London, Regno Unito
EUR 60,93
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Aggiungi al carrelloHardback. Condizione: New. 2023 ed.
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 130,42
Quantità: 15 disponibili
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Condizione: New. 1st ed. 2023 edition NO-PA16APR2015-KAP.
Da: Buchpark, Trebbin, Germania
EUR 47,25
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Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | 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.
Da: Revaluation Books, Exeter, Regno Unito
EUR 151,13
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 97 pages. 9.25x6.10x0.21 inches. In Stock.
Da: Revaluation Books, Exeter, Regno Unito
EUR 153,13
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Aggiungi al carrelloHardcover. Condizione: Brand New. 97 pages. 9.25x6.10x0.51 inches. In Stock.
Da: preigu, Osnabrück, Germania
EUR 95,25
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Deep Learning for Computational Problems in Hardware Security | Modeling Attacks on Strong Physically Unclonable Function Circuits | Pranesh Santikellur (u. a.) | Taschenbuch | xiii | Englisch | 2023 | Springer | EAN 9789811940194 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Condizione: New.
Lingua: Inglese
Editore: Springer, Springer Nature Singapore, 2023
ISBN 10: 9811940193 ISBN 13: 9789811940194
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 112,77
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Aggiungi al carrelloTaschenbuch. 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.
Da: Basi6 International, Irving, TX, U.S.A.
EUR 92,75
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Aggiungi al carrelloCondizione: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
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Da: Basi6 International, Irving, TX, U.S.A.
Condizione: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10: 9811940193 ISBN 13: 9789811940194
Da: moluna, Greven, Germania
EUR 92,27
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Aggiungi al carrelloCondizione: 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.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Springer, 2022
ISBN 10: 9811940169 ISBN 13: 9789811940163
Da: moluna, Greven, Germania
EUR 92,27
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Aggiungi al carrelloCondizione: 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.
Da: Majestic Books, Hounslow, Regno Unito
EUR 152,55
Quantità: 4 disponibili
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 153,06
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 152,87
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Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 100.
Lingua: Inglese
Editore: Springer, Springer Nature Singapore Sep 2023, 2023
ISBN 10: 9811940193 ISBN 13: 9789811940194
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 106,99
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 100 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Nature Singapore Sep 2022, 2022
ISBN 10: 9811940169 ISBN 13: 9789811940163
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 106,99
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 100 pp. Englisch.