Network Security Evaluation Method via Attack Graphs and Fuzzy Cognitive Maps BT - Intelligent Decision Technologies Proceedings of the 4th International Conference on Intelligent Decision

Aodah Diamah, Masoud Mohammadian, Bala M Balachandran

Research output: Contribution to journalArticle

Abstract

When presented with an attack graph, network administrator may raise question on how to harden the network. To defend his network, network administrator should be supplied with list of all attack paths that can compromise the network. With this list, he can decide which paths are worth paying attention to and defending against. In the event of limited resources, network administrator may only be interested in certain critical paths which cause worst network attack. Attack graph alone is not always helpful on its own and needs additional work for this purpose. In this paper we present the use of a Fuzzy Cognitive Map which is converted from attack graph with genetic algorithm to find attack scenarios causing worst impact on network security. The identified scenarios can then help network administrator to mitigate risks associated with the attack scenarios and improve his network security. Springer-Verlag Berlin Heidelberg 2012.
Original languageEnglish
Pages (from-to)433-440
Number of pages8
JournalSmart Innovation, Systems and Technologies
Volume16
DOIs
Publication statusPublished - 2012

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Network security
Genetic algorithms
Attack
Evaluation method
Fuzzy cognitive maps
Graph
Scenarios

Cite this

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title = "Network Security Evaluation Method via Attack Graphs and Fuzzy Cognitive Maps BT - Intelligent Decision Technologies Proceedings of the 4th International Conference on Intelligent Decision",
abstract = "When presented with an attack graph, network administrator may raise question on how to harden the network. To defend his network, network administrator should be supplied with list of all attack paths that can compromise the network. With this list, he can decide which paths are worth paying attention to and defending against. In the event of limited resources, network administrator may only be interested in certain critical paths which cause worst network attack. Attack graph alone is not always helpful on its own and needs additional work for this purpose. In this paper we present the use of a Fuzzy Cognitive Map which is converted from attack graph with genetic algorithm to find attack scenarios causing worst impact on network security. The identified scenarios can then help network administrator to mitigate risks associated with the attack scenarios and improve his network security. Springer-Verlag Berlin Heidelberg 2012.",
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