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Machine Intelligence and Big Data Analytics for Cybersecurity Applications: Studies in Computational Intelligence, cartea 919

Editat de Yassine Maleh, Mohammad Shojafar, Mamoun Alazab, Youssef Baddi
en Limba Engleză Paperback – 16 dec 2021
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 exploringthe latest advances on machine intelligence and big data analytics for cybersecurity applications.
 
 
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Specificații

ISBN-13: 9783030570262
ISBN-10: 3030570266
Ilustrații: XIII, 539 p. 210 illus., 172 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.77 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

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.

Textul de pe ultima copertă

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 exploringthe latest advances on machine intelligence and big data analytics for cybersecurity applications.
 
 

Caracteristici

Presents the latest discoveries in terms of machine intelligence and Big data analytics techniques and methods for cybersecurity and privacy Proposes many case studies and applications of machine intelligence in various cybersecurity fields (Smart City, IoT, Cyber Physical System, etc.) Combines theory and practice so that readers can find both a description of the concepts and context related to machine intelligence for cybersecurity