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With the recent growing number of cyberattacks and the constant lack ofeffective defense methods, cyber risks become ubiquitous in enterprisenetworks, manufacturing plants, and government computer systems.Cyber-insurance provides a valuable approach to transfer the cyber risks toinsurance companies and further improve the security status of the insured. Thedesignation of effective cyber-insurance contracts requires the considerationsfrom both the insurance market and the dynamic properties of the cyber risks.To capture the interactions between the users and the insurers, we present adynamic moral-hazard type of principal-agent model incorporated with Markovdecision processes, which are used to capture the dynamics and correlations ofthe cyber risks as well as the user's decisions on the protections. We studyand fully analyze a case with a two-state two-action user under linear coverageinsurance, and we further show the risk compensation, Peltzman effect, linearinsurance contract principle, and zero-operating profit principle in this case.Numerical experiments are provided to verify our conclusions and further extendto cases of a four-state three-action user under linear coverage insurance andthreshold coverage insurance.

Optimal Cyber-Insurance Contract Design for Dynamic Risk Management and Mitigation