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Information Fusion for Cyber-Security Analytics

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Information Fusion for Cyber-Security Analytics Synopsis

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.

About This Edition

ISBN: 9783319442563
Publication date:
Author: Izzat Alsmadi, George Karabatis, Ahmed AlEroud
Publisher: Springer an imprint of Springer International Publishing
Format: Hardback
Pagination: 379 pages
Series: Studies in Computational Intelligence
Genres: Communications engineering / telecommunications
Electronics: circuits and components
Network security
Databases
Computer security