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Multivariate dependence among cyber risks based on L-hop propagation

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  • Da, Gaofeng
  • Xu, Maochao
  • Zhao, Peng

Abstract

Dependence among cyber risks has been an essential and challenging component of risk management. The current study characterizes cyber dependence from both qualitative and quantitative perspectives based on L-hop propagation model. From the qualitative side, it is shown that cyber risks always possess positive association based on the proposed risk propagation model. From the quantitative side, an explicit formula for computing the fundamental dependence measure of covariance is provided for an arbitrary network. In particular, we study the impacts of factors—especially external and internal compromise probabilities, propagation depth, and network topologies—on dependence among cyber risks. We conclude by presenting some examples and applications.

Suggested Citation

  • Da, Gaofeng & Xu, Maochao & Zhao, Peng, 2021. "Multivariate dependence among cyber risks based on L-hop propagation," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 525-546.
    • Handle: RePEc:eee:insuma:v:101:y:2021:i:pb:p:525-546
    DOI: 10.1016/j.insmatheco.2021.09.005
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    References listed on IDEAS

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    Cited by:

    1. Na Ren & Xin Zhang, 2024. "A novel k-generation propagation model for cyber risk and its application to cyber insurance," Papers 2408.14151, arXiv.org.
    2. Loretta Mastroeni & Alessandro Mazzoccoli & Maurizio Naldi, 2023. "Cyber Insurance Premium Setting for Multi-Site Companies under Risk Correlation," Risks, MDPI, vol. 11(10), pages 1-18, September.

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    More about this item

    Keywords

    Association; Comonotonic; Covariance; Intertwined effect; Premiums;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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