Information Fusion for Cyber-Security Analytics [electronic resource] /
Contributor(s): Alsmadi, Izzat M [editor.] | Karabatis, George [editor.] | Aleroud, Ahmed [editor.] | SpringerLink (Online service).
Series: Studies in Computational Intelligence: 691Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: X, 379 p. 85 illus., 61 illus. in color. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319442570.Subject(s): Computer Engineering
| Communications Engineering, Networks | Circuits and Systems | Systems and Data Security | Big Data/AnalyticsDDC classification: 621.382 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: This book highlights several gaps that have not been addressed in existing cyber security research. It first discusses the recent attack prediction techniques that utilize one or more aspects of information to create attack prediction models. The second part is dedicated to new trends on information fusion and their applicability to cyber security; in particular, graph data analytics for cyber security, unwanted traffic detection and control based on trust management software defined networks, security in wireless sensor networks & their applications, and emerging trends in security system design using the concept of social behavioral biometric. The book guides the design of new commercialized tools that can be introduced to improve the accuracy of existing attack prediction models. Furthermore, the book advances the use of Knowledge-based Intrusion Detection Systems (IDS) to complement existing IDS technologies. It is aimed towards cyber security researchers. .
This book highlights several gaps that have not been addressed in existing cyber security research. It first discusses the recent attack prediction techniques that utilize one or more aspects of information to create attack prediction models. The second part is dedicated to new trends on information fusion and their applicability to cyber security; in particular, graph data analytics for cyber security, unwanted traffic detection and control based on trust management software defined networks, security in wireless sensor networks & their applications, and emerging trends in security system design using the concept of social behavioral biometric. The book guides the design of new commercialized tools that can be introduced to improve the accuracy of existing attack prediction models. Furthermore, the book advances the use of Knowledge-based Intrusion Detection Systems (IDS) to complement existing IDS technologies. It is aimed towards cyber security researchers. .
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