Details
| Original language | English |
|---|---|
| Pages (from-to) | 753-800 |
| Number of pages | 48 |
| Journal | Journal of Risk and Insurance |
| Volume | 91 |
| Issue number | 3 |
| Publication status | Published - 20 Aug 2024 |
Abstract
Based on classical contagion models we introduce an artificial cyber lab: the digital twin of a complex cyber system in which possible cyber resilience measures may be implemented and tested. Using the lab, in numerical case studies, we identify two classes of measures to control systemic cyber risks: security- and topology-based interventions. We discuss the implications of our findings on selected real-world cybersecurity measures currently applied in the insurance and regulation practice or under discussion for future cyber risk control. To this end, we provide a brief overview of the current cybersecurity regulation and emphasize the role of insurance companies as private regulators. Moreover, from an insurance point of view, we provide first attempts to design systemic cyber risk obligations and to measure the systemic risk contribution of individual policyholders.
Keywords
- complex systems, complexity economics, cyber insurance, cyber resilience, cybersecurity, economics of networks, systemic cyber risks
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- Accounting
- Economics, Econometrics and Finance(all)
- Finance
- Economics, Econometrics and Finance(all)
- Economics and Econometrics
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In: Journal of Risk and Insurance, Vol. 91, No. 3, 20.08.2024, p. 753-800.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Building resilience in cybersecurity
T2 - An artificial lab approach
AU - Awiszus, Kerstin
AU - Bell, Yannick
AU - Lüttringhaus, Jan
AU - Svindland, Gregor
AU - Voß, Alexander
AU - Weber, Stefan
N1 - Publisher Copyright: © 2023 The Authors. Journal of Risk and Insurance published by Wiley Periodicals LLC on behalf of American Risk and Insurance Association.
PY - 2024/8/20
Y1 - 2024/8/20
N2 - Based on classical contagion models we introduce an artificial cyber lab: the digital twin of a complex cyber system in which possible cyber resilience measures may be implemented and tested. Using the lab, in numerical case studies, we identify two classes of measures to control systemic cyber risks: security- and topology-based interventions. We discuss the implications of our findings on selected real-world cybersecurity measures currently applied in the insurance and regulation practice or under discussion for future cyber risk control. To this end, we provide a brief overview of the current cybersecurity regulation and emphasize the role of insurance companies as private regulators. Moreover, from an insurance point of view, we provide first attempts to design systemic cyber risk obligations and to measure the systemic risk contribution of individual policyholders.
AB - Based on classical contagion models we introduce an artificial cyber lab: the digital twin of a complex cyber system in which possible cyber resilience measures may be implemented and tested. Using the lab, in numerical case studies, we identify two classes of measures to control systemic cyber risks: security- and topology-based interventions. We discuss the implications of our findings on selected real-world cybersecurity measures currently applied in the insurance and regulation practice or under discussion for future cyber risk control. To this end, we provide a brief overview of the current cybersecurity regulation and emphasize the role of insurance companies as private regulators. Moreover, from an insurance point of view, we provide first attempts to design systemic cyber risk obligations and to measure the systemic risk contribution of individual policyholders.
KW - complex systems
KW - complexity economics
KW - cyber insurance
KW - cyber resilience
KW - cybersecurity
KW - economics of networks
KW - systemic cyber risks
UR - http://www.scopus.com/inward/record.url?scp=85174275049&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2211.04762
DO - 10.48550/arXiv.2211.04762
M3 - Article
AN - SCOPUS:85174275049
VL - 91
SP - 753
EP - 800
JO - Journal of Risk and Insurance
JF - Journal of Risk and Insurance
SN - 0022-4367
IS - 3
ER -