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Cyber risk measurement with ordinal data

Author

Listed:
  • Silvia Facchinetti

    (Università Cattolica del Sacro Cuore)

  • Paolo Giudici

    (University of Pavia)

  • Silvia Angela Osmetti

    (Università Cattolica del Sacro Cuore)

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.

Suggested Citation

  • Silvia Facchinetti & Paolo Giudici & Silvia Angela Osmetti, 2020. "Cyber risk measurement with ordinal data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 173-185, March.
    • Handle: RePEc:spr:stmapp:v:29:y:2020:i:1:d:10.1007_s10260-019-00470-0
    DOI: 10.1007/s10260-019-00470-0
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    References listed on IDEAS

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    Cited by:

    1. Paolo Giudici & Emanuela Raffinetti, 2021. "Cyber risk ordering with rank-based statistical models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(3), pages 469-484, September.

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