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Cyber risk measurement with ordinal data

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Abstract

The paper proposes a new methodology to measure cyber risks which, instead of using quantitative loss data, often not available, employs ordinal data. The method relies on the construction of a criticality index, whose properties are discussed and compared with alternative measures employed in operational risk measurement. The methodology is illustrated on data regarding cyber attacks collected at the worldwide level. The proposed measure is found to be quite effective to rank cyber risk types. Thus, from a policy perspective, it can be useful to guide the implementation of preventive actions.

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Notes

  1. In the loss data framework, the severity is a continuous random variable, while in the context of ordinal risk data, the severity is generally expressed on an ordinal scale, characterised by K distinct levels, ordered according to the corresponding magnitude.

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Acknowledgements

We thank the editor and two anonymous referees for useful comments and suggestions, that have improved the quality of the paper.

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Correspondence to Paolo Giudici.

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Facchinetti, S., Giudici, P. & Osmetti, S.A. Cyber risk measurement with ordinal data. Stat Methods Appl 29, 173–185 (2020). https://doi.org/10.1007/s10260-019-00470-0

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