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Dynamic structural percolation model of loss distribution for cyber risk of small and medium-sized enterprises for tree-based LAN topology

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  • Jevtić, Petar
  • Lanchier, Nicolas

Abstract

Cyber risk due to breach can be seen as a risk of a financial loss due to breach of an institution’s IT infrastructure by unauthorized parties and exploiting, taking possession of, or disclosing data assets, thus creating financial and/or reputation damage. In this paper, as a primary contribution to the existing body of actuarial literature, we propose a structural model of aggregate loss distribution for cyber risk of small and medium-sized enterprises under the assumption of a tree-based LAN topology. Up to our knowledge, there exist no theoretical models of an aggregate loss distribution for cyber risk in this setting. To achieve our goal, we contextualize the problem in the probabilistic graph-theoretical framework using percolation models. We assume that the IT network topology is represented by a random graph allowing for heterogeneous loss topology and providing instructive numerical examples.

Suggested Citation

  • Jevtić, Petar & Lanchier, Nicolas, 2020. "Dynamic structural percolation model of loss distribution for cyber risk of small and medium-sized enterprises for tree-based LAN topology," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 209-223.
    • Handle: RePEc:eee:insuma:v:91:y:2020:i:c:p:209-223
    DOI: 10.1016/j.insmatheco.2020.02.005
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    References listed on IDEAS

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    1. Eling, Martin & Jung, Kwangmin, 2018. "Copula approaches for modeling cross-sectional dependence of data breach losses," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 167-180.
    2. Martin Eling & Werner Schnell, 2016. "What do we know about cyber risk and cyber risk insurance?," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 17(5), pages 474-491, November.
    3. Spencer Wheatley & Thomas Maillart & Didier Sornette, 2016. "The extreme risk of personal data breaches and the erosion of privacy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(1), pages 1-12, January.
    4. Christian Biener & Martin Eling & Jan Hendrik Wirfs, 2015. "Insurability of Cyber Risk: An Empirical Analysis†," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 40(1), pages 131-158, January.
    5. Rob Kaas & Marc Goovaerts & Jan Dhaene & Michel Denuit, 2008. "Modern Actuarial Risk Theory," Springer Books, Springer, edition 2, number 978-3-540-70998-5, September.
    6. Fahrenwaldt, Matthias A. & Weber, Stefan & Weske, Kerstin, 2018. "Pricing Of Cyber Insurance Contracts In A Network Model," ASTIN Bulletin, Cambridge University Press, vol. 48(3), pages 1175-1218, September.
    7. T. Maillart & D. Sornette, 2010. "Heavy-tailed distribution of cyber-risks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 357-364, June.
    8. Maochao Xu & Lei Hua, 2019. "Cybersecurity Insurance: Modeling and Pricing," North American Actuarial Journal, Taylor & Francis Journals, vol. 23(2), pages 220-249, April.
    9. Eling, Martin & Loperfido, Nicola, 2017. "Data breaches: Goodness of fit, pricing, and risk measurement," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 126-136.
    10. Spencer Wheatley & Thomas Maillart & Didier Sornette, 2016. "The extreme risk of personal data breaches and the erosion of privacy," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(1), pages 1-12, January.
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    Cited by:

    1. Zhang, Xiaoyu & Xu, Maochao & Su, Jianxi & Zhao, Peng, 2023. "Structural models for fog computing based internet of things architectures with insurance and risk management applications," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1273-1291.
    2. Petar Jevtic & Nicolas Lanchier, 2021. "Probabilistic Framework For Loss Distribution Of Smart Contract Risk," Papers 2101.08964, arXiv.org.
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    5. Zängerle, Daniel & Schiereck, Dirk, 2022. "Modelling and predicting enterprise‑level cyber risks in the context of sparse data availability," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 136276, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

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