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Añadir al carritoCondición: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Idioma: Inglés
Publicado por Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3030941809 ISBN 13: 9783030941802
Librería: moluna, Greven, Alemania
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Añadir al carritoKartoniert / Broschiert. Condición: New.
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Publicado por Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10: 3030941779 ISBN 13: 9783030941772
Librería: moluna, Greven, Alemania
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Añadir al carritoPaperback. Condición: Brand New. 175 pages. 9.25x6.10x0.38 inches. In Stock.
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Añadir al carritoTaschenbuch. Condición: Neu. Machine Learning for Embedded System Security | Basel Halak | Taschenbuch | xv | Englisch | 2023 | Springer | EAN 9783030941802 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer International Publishing, 2023
ISBN 10: 3030941809 ISBN 13: 9783030941802
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.
Idioma: Inglés
Publicado por Springer International Publishing, 2022
ISBN 10: 3030941779 ISBN 13: 9783030941772
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing Apr 2022, 2022
ISBN 10: 3030941779 ISBN 13: 9783030941772
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities. 176 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing Apr 2023, 2023
ISBN 10: 3030941809 ISBN 13: 9783030941802
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities. 176 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: New. PRINT ON DEMAND.
Idioma: Inglés
Publicado por Springer, Springer Apr 2023, 2023
ISBN 10: 3030941809 ISBN 13: 9783030941802
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 176 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Springer Apr 2022, 2022
ISBN 10: 3030941779 ISBN 13: 9783030941772
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 176 pp. Englisch.