Reducing Informational Disadvantages to Improve Cyber Risk Management†

Sachin Shetty, Michael McShane (), Linfeng Zhang, Jay P. Kesan, Charles A. Kamhoua, Kevin Kwiat and Laurent L. Njilla
Additional contact information
Sachin Shetty: Old Dominion University
Michael McShane: Old Dominion University
Linfeng Zhang: University of Illinois at Urbana-Champaign
Jay P. Kesan: University of Illinois at Urbana-Champaign
Charles A. Kamhoua: Air Force Research Lab
Kevin Kwiat: Air Force Research Lab
Laurent L. Njilla: Air Force Research Lab

The Geneva Papers on Risk and Insurance - Issues and Practice, 2018, vol. 43, issue 2, No 4, 224-238

Abstract: Abstract Effective cyber risk management should include the use of insurance not only to transfer cyber risk but also to provide incentives for insured enterprises to invest in cyber self-protection. Research indicates that asymmetric information, correlated loss, and interdependent security issues make this difficult if insurers cannot monitor the cybersecurity efforts of the insured enterprises. To address this problem, this paper proposes the Cyber Risk Scoring and Mitigation (CRISM) tool, which estimates cyberattack probabilities by directly monitoring and scoring cyber risk based on assets at risk and continuously updated software vulnerabilities. CRISM also produces risk scores that allow organisations to optimally choose mitigation policies that can potentially reduce insurance premiums.

Keywords: cyber risk management; cyber insurance; vulnerability assessment; security risk scores; Bayesian belief networks; attack graphs (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1057/s41288-018-0078-3

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