Intelligent Risk Identification and Analysis in IT Network Systems

Masoud Mohammadian

doi:10.1007/978-3-642-23960-1_44

Intelligent Risk Identification and Analysis in IT Network Systems

Masoud Mohammadian

Canberra Business School

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

With ever increasing application of information technologies in every day activities, organizations face the need for applications that provides better security. The existence of complex IT systems with multiple interdependencies creates great difficulties for Chief Security Officers to comprehend and be aware of all potential risks in such systems. Intelligent decision making for IT security is a crucial element of an organization’s success and its competitive position in the marketplace. This paper considers the implementation of an integrated attack graph and a Fuzzy Cognitive Maps (FCM) to provide facilities to capture and represent complex relationships in IT systems. By using FCMs the security of IT systems can regularly be reviewed and improved. What-if analysis can be performed to better understand vulnerabilities of a designed system. Finally an integrated system consisting of FCM, Attack graphs and Genetic Algorithms (GA) is used to identify vulnerabilities of IT systems that may not be apparent to Chief Security Officers.

Original language	English
Title of host publication	Artificial Intelligence Applications and Innovations - 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer
Subtitle of host publication	IFIP Advances in Information and Communication Technology
Editors	Lazaros Iliadis, Ilias Maglogiannis, Harris Papadopoulos
Place of Publication	Berlin, Heidelberg, Germany
Publisher	Springer
Pages	370-377
Number of pages	8
Volume	364
ISBN (Electronic)	9783642239601
ISBN (Print)	9783642239595
DOIs	https://doi.org/10.1007/978-3-642-23960-1_44
Publication status	Published - 2011
Event	Artificial Intelligence Applications and Innovations: 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer - Corfu, Corfu, Greece Duration: 15 Sept 2011 → 18 Sept 2011

Conference

Conference	Artificial Intelligence Applications and Innovations: 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer
Country/Territory	Greece
City	Corfu
Period	15/09/11 → 18/09/11

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10.1007/978-3-642-23960-1_44

http://dl.ifip.org/db/conf/ifip12/aiai2011-2/Mohammadian11.pdf

Cite this

Mohammadian, M. (2011). Intelligent Risk Identification and Analysis in IT Network Systems. In L. Iliadis, I. Maglogiannis, & H. Papadopoulos (Eds.), Artificial Intelligence Applications and Innovations - 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer: IFIP Advances in Information and Communication Technology (Vol. 364, pp. 370-377). Springer. https://doi.org/10.1007/978-3-642-23960-1_44

Mohammadian, Masoud. / Intelligent Risk Identification and Analysis in IT Network Systems. Artificial Intelligence Applications and Innovations - 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer: IFIP Advances in Information and Communication Technology. editor / Lazaros Iliadis ; Ilias Maglogiannis ; Harris Papadopoulos. Vol. 364 Berlin, Heidelberg, Germany : Springer, 2011. pp. 370-377

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abstract = "With ever increasing application of information technologies in every day activities, organizations face the need for applications that provides better security. The existence of complex IT systems with multiple interdependencies creates great difficulties for Chief Security Officers to comprehend and be aware of all potential risks in such systems. Intelligent decision making for IT security is a crucial element of an organization{\textquoteright}s success and its competitive position in the marketplace. This paper considers the implementation of an integrated attack graph and a Fuzzy Cognitive Maps (FCM) to provide facilities to capture and represent complex relationships in IT systems. By using FCMs the security of IT systems can regularly be reviewed and improved. What-if analysis can be performed to better understand vulnerabilities of a designed system. Finally an integrated system consisting of FCM, Attack graphs and Genetic Algorithms (GA) is used to identify vulnerabilities of IT systems that may not be apparent to Chief Security Officers.",

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Mohammadian, M 2011, Intelligent Risk Identification and Analysis in IT Network Systems. in L Iliadis, I Maglogiannis & H Papadopoulos (eds), Artificial Intelligence Applications and Innovations - 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer: IFIP Advances in Information and Communication Technology. vol. 364, Springer, Berlin, Heidelberg, Germany, pp. 370-377, Artificial Intelligence Applications and Innovations: 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer, Corfu, Greece, 15/09/11. https://doi.org/10.1007/978-3-642-23960-1_44

Intelligent Risk Identification and Analysis in IT Network Systems. / Mohammadian, Masoud.
Artificial Intelligence Applications and Innovations - 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer: IFIP Advances in Information and Communication Technology. ed. / Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. Vol. 364 Berlin, Heidelberg, Germany: Springer, 2011. p. 370-377.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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AB - With ever increasing application of information technologies in every day activities, organizations face the need for applications that provides better security. The existence of complex IT systems with multiple interdependencies creates great difficulties for Chief Security Officers to comprehend and be aware of all potential risks in such systems. Intelligent decision making for IT security is a crucial element of an organization’s success and its competitive position in the marketplace. This paper considers the implementation of an integrated attack graph and a Fuzzy Cognitive Maps (FCM) to provide facilities to capture and represent complex relationships in IT systems. By using FCMs the security of IT systems can regularly be reviewed and improved. What-if analysis can be performed to better understand vulnerabilities of a designed system. Finally an integrated system consisting of FCM, Attack graphs and Genetic Algorithms (GA) is used to identify vulnerabilities of IT systems that may not be apparent to Chief Security Officers.

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Mohammadian M. Intelligent Risk Identification and Analysis in IT Network Systems. In Iliadis L, Maglogiannis I, Papadopoulos H, editors, Artificial Intelligence Applications and Innovations - 12th INNS EANN - SIG International Conference, EANN 2011 and 7th IFIP WG 12.5 International Confer: IFIP Advances in Information and Communication Technology. Vol. 364. Berlin, Heidelberg, Germany: Springer. 2011. p. 370-377 doi: 10.1007/978-3-642-23960-1_44

Intelligent Risk Identification and Analysis in IT Network Systems

Abstract

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