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Information fusion for cyber-security analytics

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...

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Detalles Bibliográficos
Autores principales: Alsmadi, Izzat, Karabatis, George, Aleroud, Ahmed
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-44257-0
http://cds.cern.ch/record/2240627
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author Alsmadi, Izzat
Karabatis, George
Aleroud, Ahmed
author_facet Alsmadi, Izzat
Karabatis, George
Aleroud, Ahmed
author_sort Alsmadi, Izzat
collection CERN
description 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. .
id cern-2240627
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
publisher Springer
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spelling cern-22406272021-04-21T19:23:25Zdoi:10.1007/978-3-319-44257-0http://cds.cern.ch/record/2240627engAlsmadi, IzzatKarabatis, GeorgeAleroud, AhmedInformation fusion for cyber-security analyticsEngineeringThis 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. .Springeroai:cds.cern.ch:22406272017
spellingShingle Engineering
Alsmadi, Izzat
Karabatis, George
Aleroud, Ahmed
Information fusion for cyber-security analytics
title Information fusion for cyber-security analytics
title_full Information fusion for cyber-security analytics
title_fullStr Information fusion for cyber-security analytics
title_full_unstemmed Information fusion for cyber-security analytics
title_short Information fusion for cyber-security analytics
title_sort information fusion for cyber-security analytics
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-44257-0
http://cds.cern.ch/record/2240627
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AT karabatisgeorge informationfusionforcybersecurityanalytics
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