Intelligent security and risk analysis in network systems

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

Network security architects devote a considerable time and efforts in improving the security of their data and networks. Attack graph are graphical representation of networks that can assist in documenting risks in network systems. Attack graphs need to be analysed and tested to remove security risks in a network. All comprising paths identified on an attack graph are listed for close attention and consideration of how to protect against possible attacks. There is a need for an automated system that can generate and evaluate attack paths and provide security architects with decision making tools that provides them with details of paths that an attacker may take to attack a network and cause damage and security breaches in their networks. Such an automated system can provide paths that can cause the most undesirable attacks. In this research paper an automated system using Fuzzy Cognitive Maps developed by Mohammadian [3] for identifying attack paths from attack graphs are presented. A novel decision making approach to determine time delay for an attacker to reach resources in a network is considered. A multilayer Fuzzy Logic is employed for the development of calculation of time delay for an attacker to reach a resource once it has access to a network.

Original languageEnglish
Title of host publication2017 International Conference on Infocom Technologies and Unmanned Systems
Subtitle of host publicationTrends and Future Directions, ICTUS 2017
Place of PublicationDubai, UAE
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages825-830
Number of pages6
Volume2018-January
ISBN (Electronic)9781538605141
ISBN (Print)9781538605158
DOIs
Publication statusPublished - 18 Dec 2017
Event2017 International Conference on Infocom Technologies and Unmanned Systems, ICTUS 2017 - Dubai, United Arab Emirates
Duration: 18 Dec 201720 Dec 2017

Publication series

Name2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017
Volume2018-January

Conference

Conference2017 International Conference on Infocom Technologies and Unmanned Systems, ICTUS 2017
CountryUnited Arab Emirates
CityDubai
Period18/12/1720/12/17

Fingerprint

Security Analysis
Risk Analysis
Risk analysis
Time delay
Decision making
Attack
Network security
Fuzzy systems
Security of data
Fuzzy logic
Multilayers
Path
Graph in graph theory
Time Delay
Decision Making
Fuzzy Cognitive Maps
Security analysis
Resources
Network Security
Graphical Representation

Cite this

Mohammadian, M. (2017). Intelligent security and risk analysis in network systems. In 2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017 (Vol. 2018-January, pp. 825-830). (2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017; Vol. 2018-January). Dubai, UAE: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICTUS.2017.8286120
Mohammadian, Masoud. / Intelligent security and risk analysis in network systems. 2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017. Vol. 2018-January Dubai, UAE : IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 825-830 (2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017).
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abstract = "Network security architects devote a considerable time and efforts in improving the security of their data and networks. Attack graph are graphical representation of networks that can assist in documenting risks in network systems. Attack graphs need to be analysed and tested to remove security risks in a network. All comprising paths identified on an attack graph are listed for close attention and consideration of how to protect against possible attacks. There is a need for an automated system that can generate and evaluate attack paths and provide security architects with decision making tools that provides them with details of paths that an attacker may take to attack a network and cause damage and security breaches in their networks. Such an automated system can provide paths that can cause the most undesirable attacks. In this research paper an automated system using Fuzzy Cognitive Maps developed by Mohammadian [3] for identifying attack paths from attack graphs are presented. A novel decision making approach to determine time delay for an attacker to reach resources in a network is considered. A multilayer Fuzzy Logic is employed for the development of calculation of time delay for an attacker to reach a resource once it has access to a network.",
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Mohammadian, M 2017, Intelligent security and risk analysis in network systems. in 2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017. vol. 2018-January, 2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017, vol. 2018-January, IEEE, Institute of Electrical and Electronics Engineers, Dubai, UAE, pp. 825-830, 2017 International Conference on Infocom Technologies and Unmanned Systems, ICTUS 2017, Dubai, United Arab Emirates, 18/12/17. https://doi.org/10.1109/ICTUS.2017.8286120

Intelligent security and risk analysis in network systems. / Mohammadian, Masoud.

2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017. Vol. 2018-January Dubai, UAE : IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 825-830 (2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017; Vol. 2018-January).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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Mohammadian M. Intelligent security and risk analysis in network systems. In 2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017. Vol. 2018-January. Dubai, UAE: IEEE, Institute of Electrical and Electronics Engineers. 2017. p. 825-830. (2017 International Conference on Infocom Technologies and Unmanned Systems: Trends and Future Directions, ICTUS 2017). https://doi.org/10.1109/ICTUS.2017.8286120