A Multivariate Model to Quantify and Mitigate Cybersecurity Risk

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ID: 116146
2020
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Abstract
The cost of cybersecurity incidents is large and growing. However, conventional methods for measuring loss and choosing mitigation strategies use simplifying assumptions and are often not supported by cyber attack data. In this paper, we present a multivariate model for different, dependent types of attack and the effect of mitigation strategies on those attacks. Utilising collected cyber attack data and assumptions on mitigation approaches, we look at an example of using the model to optimise the choice of mitigations. We find that the optimal choice of mitigations will depend on the goal—to prevent extreme damages or damage on average. Numerical experiments suggest the dependence aspect is important and can alter final risk estimates by as much as 30%. The methodology can be used to quantify the cost of cyber attacks and support decision making on the choice of optimal mitigation strategies.
Reference Key
bentley2020risksa Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Mark Bentley;Alec Stephenson;Peter Toscas;Zili Zhu;Bentley, Mark;Stephenson, Alec;Toscas, Peter;Zhu, Zili;
Journal risks
Year 2020
DOI
10.3390/risks8020061
URL
https://www.mdpi.com/2227-9091/8/2/61/htm
Keywords
value at risk (var) cyber risk optimal mitigations operational risk

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