國立虎尾科技大學 |

Information fusion for cyber-security analytics

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Information fusion for cyber-security analytics/ edited by Izzat M Alsmadi, George Karabatis, Ahmed Aleroud.
其他作者:	Alsmadi, Izzat M.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	x, 379 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Intrusion detection systems (Computer security) -
電子資源:	http://dx.doi.org/10.1007/978-3-319-44257-0
ISBN:	9783319442570

Information fusion for cyber-security analytics
Information fusion for cyber-security analytics[electronic resource] /edited by Izzat M Alsmadi, George Karabatis, Ahmed Aleroud. - Cham :Springer International Publishing :2017. - x, 379 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.6911860-949X ;. - Studies in computational intelligence ;v. 50. .

Introduction -- Part 1: Information Fusion for Cyber-Security Analytics -- Activity Information Fusion for Security Analytics -- Location Information Fusion for Security Analytics -- Time Information Fusion for Security Analytics -- Individuality Information Fusion for Security Analytics -- Relation Information Fusion for Security Analytics -- Part 2: Trends in Using Information Fusion Techniques to Discover Cyber Threats -- Big Data Fusion for Predicting Network Threats -- Using Software Defined Networks for Cyber Threat Discovery -- Privacy Preserving Information Fusion for Analyzing Network Data -- Using Information Fusion to Discover Zero-Day Attacks -- Enhancing Social Network Privacy and Security Using Graph-based Data Fusion -- Using Information Fusion to discover Cyber-threats in Wireless Sensor Networks -- Information Fusion for Improving Privacy and Security in Healthcare Applications -- Predicting Social Engineering Attacks Using Information Fusion Techniques -- Part 3: Applications and tools. -Information Fusion Application and Tools for Cyber Security Analytics -- Conclusion.

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.

ISBN: 9783319442570

Standard No.: 10.1007/978-3-319-44257-0doiSubjects--Topical Terms:

784166
Intrusion detection systems (Computer security)

LC Class. No.: TK5105.59

Dewey Class. No.: 005.8

Information fusion for cyber-security analytics
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505 0 $a Introduction -- Part 1: Information Fusion for Cyber-Security Analytics -- Activity Information Fusion for Security Analytics -- Location Information Fusion for Security Analytics -- Time Information Fusion for Security Analytics -- Individuality Information Fusion for Security Analytics -- Relation Information Fusion for Security Analytics -- Part 2: Trends in Using Information Fusion Techniques to Discover Cyber Threats -- Big Data Fusion for Predicting Network Threats -- Using Software Defined Networks for Cyber Threat Discovery -- Privacy Preserving Information Fusion for Analyzing Network Data -- Using Information Fusion to Discover Zero-Day Attacks -- Enhancing Social Network Privacy and Security Using Graph-based Data Fusion -- Using Information Fusion to discover Cyber-threats in Wireless Sensor Networks -- Information Fusion for Improving Privacy and Security in Healthcare Applications -- Predicting Social Engineering Attacks Using Information Fusion Techniques -- Part 3: Applications and tools. -Information Fusion Application and Tools for Cyber Security Analytics -- Conclusion.
520 $a 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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