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Cybersecurity Insurance: Modeling and Pricing

Author

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  • Maochao Xu
  • Lei Hua

Abstract

Cybersecurity risk has attracted considerable attention in recent decades. However, the modeling of cybersecurity risk is still in its infancy, mainly because of its unique characteristics. In this study, we develop a framework for modeling and pricing cybersecurity risk. The proposed model consists of three components: the epidemic model, loss function, and premium strategy. We study the dynamic upper bounds for the infection probabilities based on both Markov and non-Markov models. A simulation approach is proposed to compute the premium for cybersecurity risk for practical use. The effects of different infection distributions and dependence among infection processes on the losses are also studied.

Suggested Citation

  • Maochao Xu & Lei Hua, 2019. "Cybersecurity Insurance: Modeling and Pricing," North American Actuarial Journal, Taylor & Francis Journals, vol. 23(2), pages 220-249, April.
    • Handle: RePEc:taf:uaajxx:v:23:y:2019:i:2:p:220-249
    DOI: 10.1080/10920277.2019.1566076
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    Citations

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    Cited by:

    1. Malavasi, Matteo & Peters, Gareth W. & Shevchenko, Pavel V. & Trück, Stefan & Jang, Jiwook & Sofronov, Georgy, 2022. "Cyber risk frequency, severity and insurance viability," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 90-114.
    2. Mazaher Kianpour & Stewart J. Kowalski & Harald Øverby, 2021. "Systematically Understanding Cybersecurity Economics: A Survey," Sustainability, MDPI, vol. 13(24), pages 1-28, December.
    3. Zhang, Xiaoyu & Xu, Maochao & Da, Gaofeng & Zhao, Peng, 2021. "Ensuring confidentiality and availability of sensitive data over a network system under cyber threats," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    4. 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.
    5. 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.
    6. Yeftanus Antonio & Sapto Wahyu Indratno & Rinovia Simanjuntak, 2021. "Cyber Insurance Ratemaking: A Graph Mining Approach," Risks, MDPI, vol. 9(12), pages 1-34, December.
    7. Alessandro Mazzoccoli & Maurizio Naldi, 2022. "An Overview of Security Breach Probability Models," Risks, MDPI, vol. 10(11), pages 1-29, November.
    8. Gabriela Zeller & Matthias Scherer, 2023. "Risk mitigation services in cyber insurance: optimal contract design and price structure," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 502-547, April.
    9. 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.
    10. João Vinícius de França Carvalho & Eduardo Flores & Emiliano A. Valdez, 2022. "The Relevance and Challenges of the Insurance Industry in Contemporary Administration: A Call for Researchers," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 26(3), pages 210313-2103.
    11. Yeftanus Antonio & Sapto Wahyu Indratno & Suhadi Wido Saputro, 2021. "Pricing of cyber insurance premiums using a Markov-based dynamic model with clustering structure," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-28, October.
    12. Kerstin Awiszus & Yannick Bell & Jan Luttringhaus & Gregor Svindland & Alexander Vo{ss} & Stefan Weber, 2022. "Building Resilience in Cybersecurity -- An Artificial Lab Approach," Papers 2211.04762, arXiv.org, revised Sep 2023.

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