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dc.contributor.authorBuczkowski, Pen_US
dc.contributor.authorMalacaria, Pen_US
dc.contributor.authorHankin, Cen_US
dc.contributor.authorFielder, Aen_US
dc.date.accessioned2023-02-17T10:19:25Z
dc.date.issued2022-04-28en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/84505
dc.description.abstractCySecTool is a tool that finds a cost-optimal security controls portfolio in a given budget for a probabilistic attack graph. A portfolio is a set of counter-measures, or controls, against vulnerabilities adopted for a computer system, while an attack graph is a type of a threat scenario model. In an attack graph, nodes are privilege states of the attacker, edges are vulnerabilities escalating privileges, and controls reduce the probabilities of some vulnerabilities being exploited. The tool builds on an optimisation algorithm published by Khouzani et al., enabling a user to quickly create, edit, and incrementally improve models, analyse results for given portfolios and display the best solutions for all possible budgets in the form of a Pareto frontier. A case study was performed utilising a system graph and suspected attack paths prepared by industrial security engineers based on an industrial source with which they work. The goal of the case study is to model a supervisory control and data acquisition (SCADA) industrial system which, due to having a potential to harm people, necessitates strong protection while not allowing to use of typical penetration tools like vulnerability scanners. Results are analysed to show how a cyber-security analyst would use CySecTool to store cyber-security intelligence and draw further conclusions.en_US
dc.format.extent21 - 30 (10)en_US
dc.publisherAssociation for Computing Machineryen_US
dc.rightsThis item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectindustrial control systemen_US
dc.subjectmulti-objective optimisationen_US
dc.subjectcybersecurity risk assessment toolen_US
dc.subjectthreat modellingen_US
dc.subjectprobabilistic attack graphen_US
dc.titleOptimal Security Hardening over a Probabilistic Attack Graph: A Case Study of an Industrial Control System using CySecToolen_US
dc.typeConference Proceeding
dc.rights.holder© 2022 Owner/Author
dc.identifier.doi10.1145/3510547.3517919en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.publisher-urlhttps://dl.acm.org/doi/10.1145/3510547.3517919en_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US


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This item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Except where otherwise noted, this item's license is described as This item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.