Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the state of the art in cybersecurity, and critically reviews existing approaches &nbsp Addresses the intersection of two hot topics: cybersecurity and data science Includes an essential introduction to field. Seller Inventory # 448681025

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Data Science in Cybersecurity and Cyberthreat Intelligence

Kim-Kwang Raymond Choo

Published by Springer International Publishing Feb 2020, 2020

ISBN 10: 3030387879 ISBN 13: 9783030387877

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany

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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms. 144 pp. Englisch. Seller Inventory # 9783030387877

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Data Science in Cybersecurity and Cyberthreat Intelligence

Kim-Kwang Raymond Choo

Published by Springer International Publishing, 2020

ISBN 10: 3030387879 ISBN 13: 9783030387877

New Hardcover

Seller: AHA-BUCH GmbH, Einbeck, Germany

Seller rating 5 out of 5 stars

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms. Seller Inventory # 9783030387877

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