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Synopsis
Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms.
This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work.
Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks.
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- ÉditeurSpringer-Verlag New York Inc.
- Date d'édition2009
- ISBN 10 0387887342
- ISBN 13 9780387887340
- ReliureRelié
- Langueanglais
- Nombre de pages362
- ÉditeurTsai Jeffrey J. P., Yu Philip S.
- Coordonnées du fabricantnon disponible
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Machine Learning in Cyber Trust: Security, Privacy, and Reliability
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SPRINGER NATURE, 2009
ISBN 10 : 0387887342
ISBN 13 : 9780387887340
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Etat : Sehr gut. Zustand: Sehr gut | Seiten: 362 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 4703957/2
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Machine Learning in Cyber Trust: Security, Privacy, and Reliability
Edité par
Springer-Verlag New York Inc, 2009
ISBN 10 : 0387887342
ISBN 13 : 9780387887340
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Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Hardcover. Etat : Brand New. 1st edition. 378 pages. 9.50x6.25x1.00 inches. In Stock. N° de réf. du vendeur __0387887342
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Machine Learning in Cyber Trust
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Machine Learning in Cyber Trust : Security, Privacy, and Reliability
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Springer Us Apr 2009, 2009
ISBN 10 : 0387887342
ISBN 13 : 9780387887340
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Buch. Etat : Neu. Neuware - Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms.This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work.Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks. N° de réf. du vendeur 9780387887340
Quantité disponible : 1 disponible(s)
Image d'archives
Machine Learning in Cyber Trust: Security, Privacy, and Reliability
Edité par
Springer-Verlag New York Inc, 2009
ISBN 10 : 0387887342
ISBN 13 : 9780387887340
Neuf
Couverture rigide
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : Brand New. 1st edition. 378 pages. 9.50x6.25x1.00 inches. In Stock. N° de réf. du vendeur x-0387887342
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Machine Learning in Cyber Trust (Hardcover)
Edité par
Springer-Verlag New York Inc., New York, NY, 2009
ISBN 10 : 0387887342
ISBN 13 : 9780387887340
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Vendeur : Grand Eagle Retail, Fairfield, OH, Etats-Unis
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Hardcover. Etat : new. Hardcover. Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms.This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work.Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks. In cyber-based systems, tasks can be formulated as learning problems and approached as machine-learning algorithms. This book covers applications of machine-learning methods in reliability, security, performance and privacy issues in cyber space. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780387887340
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