IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v45y2018i15p2718-2740.html
   My bibliography  Save this article

Modeling multivariate cybersecurity risks

Author

Listed:
  • Chen Peng
  • Maochao Xu
  • Shouhuai Xu
  • Taizhong Hu

Abstract

Modeling cybersecurity risks is an important, yet challenging, problem. In this paper, we initiate the study of modeling multivariate cybersecurity risks. We develop the first statistical approach, which is centered at a Copula-GARCH model that uses vine copulas to model the multivariate dependence exhibited by real-world cyber attack data. We find that ignoring the due multivariate dependence causes a severe underestimation of cybersecurity risks. Both simulation and empirical studies show that the proposed approach leads to accurate predictions of multivariate cybersecurity risks.

Suggested Citation

  • Chen Peng & Maochao Xu & Shouhuai Xu & Taizhong Hu, 2018. "Modeling multivariate cybersecurity risks," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(15), pages 2718-2740, November.
    • Handle: RePEc:taf:japsta:v:45:y:2018:i:15:p:2718-2740
    DOI: 10.1080/02664763.2018.1436701
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2018.1436701
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2018.1436701?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. Blakely, Benjamin & Kurtenbach, Jim & Nowak, Lovila, 2022. "Exploring the information content of cyber breach reports and the relationship to internal controls," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
    4. Ding, Weiyong & Xu, Maochao & Huang, Yu & Zhao, Peng & Song, Fengyi, 2021. "Cyber attacks on PMU placement in a smart grid: Characterization and optimization," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    5. Daniel Zängerle & Dirk Schiereck, 2023. "Modelling and predicting enterprise-level cyber risks in the context of sparse data availability," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(2), pages 434-462, April.
    6. 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.
    7. Dacorogna, Michel & Debbabi, Nehla & Kratz, Marie, 2023. "Building up cyber resilience by better grasping cyber risk via a new algorithm for modelling heavy-tailed data," European Journal of Operational Research, Elsevier, vol. 311(2), pages 708-729.
    8. Ma, Boyuan & Chu, Tingjin & Jin, Zhuo, 2022. "Frequency and severity estimation of cyber attacks using spatial clustering analysis," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 33-45.
    9. 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).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:japsta:v:45:y:2018:i:15:p:2718-2740. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.