Cyber risk ordering with rank-based statistical models

Paolo Giudici and Emanuela Raffinetti ()
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Emanuela Raffinetti: Università degli Studi di Milano

AStA Advances in Statistical Analysis, 2021, vol. 105, issue 3, No 5, 469-484

Abstract: Abstract In a world that is increasingly connected on-line, cyber risks become critical. Cyber risk management is very difficult, as cyber loss data are typically not disclosed. To mitigate the reputational risks associated with their disclosure, loss data may be collected in terms of ordered severity levels. However, to date, there are no risk models for ordinal cyber data. We fill the gap, proposing a rank-based statistical model aimed at predicting the severity levels of cyber risks. The application of our approach to a real-world case shows that the proposed models are, while statistically sound, simple to implement and interpret.

Keywords: Cyber attacks; Concordance measures; Operational risks; Ordinal data; Rank regression (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10182-020-00387-0

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