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Modelling cyber-security experts' decision making processes using aggregation operators

Miller, Simon; Wagner, Christian; Aickelin, Uwe; Garibaldi, Jonathan M.

Authors

Simon Miller

Uwe Aickelin



Abstract

An important role carried out by cyber-security experts is the assessment of proposed computer systems, during their design stage. This task is fraught with difficulties and uncertainty, making the knowledge provided by human experts essential for successful assessment. Today, the increasing number of progressively complex systems has led to an urgent need to produce tools that support the expert-led process of system-security assessment. In this research, we use Weighted Averages (WAs) and Ordered Weighted Averages (OWAs) with Evolutionary Algorithms (EAs) to create aggregation operators that model parts of the assessment process. We show how individual overall ratings for security components can be produced from ratings of their characteristics, and how these individual overall ratings can be aggregated to produce overall rankings of potential attacks on a system. As well as the identification of salient attacks and weak points in a prospective system, the proposed method also highlights which factors and security components contribute most to a component's difficulty and attack ranking respectively. A real world scenario is used in which experts were asked to rank a set of technical attacks, and to answer a series of questions about the security components that are the subject of the attacks. The work shows how finding good aggregation operators, and identifying important components and factors of a cyber-security problem can be automated. The resulting operators have the potential for use as decision aids for systems designers and cyber-security experts, increasing the amount of assessment that can be achieved with the limited resources available.

Citation

Miller, S., Wagner, C., Aickelin, U., & Garibaldi, J. M. (2016). Modelling cyber-security experts' decision making processes using aggregation operators. Computers and Security, 62, 229-245. https://doi.org/10.1016/j.cose.2016.08.001

Journal Article Type Article
Acceptance Date Aug 3, 2016
Online Publication Date Aug 10, 2016
Publication Date 2016-09
Deposit Date Aug 16, 2016
Publicly Available Date Aug 16, 2016
Journal Computers & Security
Print ISSN 0167-4048
Electronic ISSN 0167-4048
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 62
Pages 229-245
DOI https://doi.org/10.1016/j.cose.2016.08.001
Keywords Expert Decision Making; Cyber-security; Evolutionary algorithm; Ordered Weighted average; Weighted Average
Public URL http://eprints.nottingham.ac.uk/id/eprint/35868
Publisher URL http://www.sciencedirect.com/science/article/pii/S016740481630089X
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by/4.0





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