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Machine intelligence and big data an...

Maleh, Yassine.

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Machine intelligence and big data analytics for cybersecurity applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine intelligence and big data analytics for cybersecurity applications/ edited by Yassine Maleh ... [et al.].
其他作者:	Maleh, Yassine.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xiii, 539 p. :ill., digital ;24 cm.
內容註:	Network Intrusion Detection: Taxonomy and Machine Learning Applications -- Machine Learning and Deep Learning models for Big Data Issues -- The Fundamentals and Potential for Cybersecurity of Big Data in the Modern World -- Improving Cyber-Threat Detection by Moving the Boundary around the Normal Samples -- Bayesian Networks for Online Threat Detection -- Network Intrusion Detection for TCP/IP Packets with Machine Learning Techniques -- Developing a Blockchain-based and Distributed Database-oriented Multi-Malware Detection Engine -- Classifying Common Vulnerabilities and Exposures Database Using Text Mining and Graph Theoretical Analysis -- Robust Cryptographical Applications for a Secure Wireless Network Protocol.
Contained By:	Springer Nature eBook
標題:	Artificial intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-57024-8
ISBN:	9783030570248

Machine intelligence and big data analytics for cybersecurity applications
Machine intelligence and big data analytics for cybersecurity applications[electronic resource] /edited by Yassine Maleh ... [et al.]. - Cham :Springer International Publishing :2021. - xiii, 539 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.9191860-949X ;. - Studies in computational intelligence ;v.919..

Network Intrusion Detection: Taxonomy and Machine Learning Applications -- Machine Learning and Deep Learning models for Big Data Issues -- The Fundamentals and Potential for Cybersecurity of Big Data in the Modern World -- Improving Cyber-Threat Detection by Moving the Boundary around the Normal Samples -- Bayesian Networks for Online Threat Detection -- Network Intrusion Detection for TCP/IP Packets with Machine Learning Techniques -- Developing a Blockchain-based and Distributed Database-oriented Multi-Malware Detection Engine -- Classifying Common Vulnerabilities and Exposures Database Using Text Mining and Graph Theoretical Analysis -- Robust Cryptographical Applications for a Secure Wireless Network Protocol.

This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today's IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, it aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and big data analytics for cybersecurity applications.

ISBN: 9783030570248

Standard No.: 10.1007/978-3-030-57024-8doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: Q335 / .M33 2021

Dewey Class. No.: 006.3

Machine intelligence and big data analytics for cybersecurity applications
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520 $a This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today's IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, it aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and big data analytics for cybersecurity applications.
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