Cybersecurity Insurance: Modeling and Pricing

References

• Barrat, A., M. Barthlemy, and A. Vespignani. 2008. Dynamical processes on complex networks. Cambridge: Cambridge University Press.
   Google Scholar
• Betterley., R. S. 2016. Cyber / privacy insurance market survey: A tough market for larger insureds, but smaller insureds finding eager insurers. Betterley Report, June.
   Google Scholar
• Böhme, R., and G. Kataria. 2006. “Models and measures for correlation in cyber-insurance.” In Fifth workshop on the economics of information security. University of Cambridge, England.
   Google Scholar
• Böhme, R., and G. Schwartz. 2010. “Modeling cyber-insurance: Towards a unifying framework.” In Nineth workshop on the economics of information security. Harvard University, USA.
   Google Scholar
• Cator, E., R. Bovenkamp, and P. V. Mieghem. 2013. Susceptible-infected-susceptible epidemics on networks with general infection and cure times. Physical Review E 87(6):062816.
   Web of Science ®Google Scholar
• Cator, E., and P. V. Mieghem. 2014. Nodal infection in markovian susceptible-infected-susceptible and susceptible-infected-removed epidemics on networks are non-negatively correlated. Physical Review E 89(5):052802.
   Web of Science ®Google Scholar
• Chapanond, A., M. S. Krishnamoorthy, and B. Yener. 2005. Graph theoretic and spectral analysis of Enron email data. Computational & Mathematical Organization Theory 11: 265–281.
   Google Scholar
• Coddington, E. A. 2012. An introduction to ordinary differential equations. Indianapolis: Courier Corporation.
   Google Scholar
• Department of Homeland Security (DHS). Cybersecurity insurance. www.dhs.gov/publication/cybersecurity-insurance.
   Google Scholar
• Doerr, C., N. Blenn, and P. V. Mieghem. 2013. Lognormal infection times of online information spread. PloS ONE 8(5):e64349.
   PubMed Web of Science ®Google Scholar
• Eling, M., and W. Schnell. 2016. What do we know about cyber risk and cyber risk insurance? Journal of Risk Finance 17: 474–491.
   Web of Science ®Google Scholar
• Gordon, L. A., M. P. Loeb, and T. Sohail. 2003. A framework for using insurance for cyber-risk management. Communications of the ACM 46: 81–85.
   Web of Science ®Google Scholar
• Herath, V. S. B., and T. C. Herath. 2011. Copula-based actuarial model for pricing cyber-insurance policies. Insurance Markets and Companies: Analyses and Actuarial Computations 2: 7–20.
   Google Scholar
• Joe, H. 2014. Dependence modeling with copulas. CRC Press. Boca Raton, FL.
   Google Scholar
• Karlin., S. 2014. A first course in stochastic processes. New Pork: Academic Press.
   Google Scholar
• Kosub, T. 2015. Components and challenges of integrated cyber risk management. Zeitschrift für die gesamte Versicherungswissenschaft 104: 615–634.
   Google Scholar
• Martens, M., H. Asghari, H., M. Eeten, and P. V. Mieghem. 2016. A time-dependent SIS-model for long-term computer worm evolution. In IEEE Conference on Communications and network security (CNS), 207–215.
   Google Scholar
• Mieghem, P. V. 2014. Performance analysis of complex networks and systems. Cambridge: Cambridge University Press.
   Google Scholar
• Mieghem, P. V., and R. V. Bovenkamp. 2013. Non-Markovian infection spread dramatically alters the susceptible-infected-susceptible epidemic threshold in networks. Physical Review Letters 110(10):108701-1–108701-5.
   Web of Science ®Google Scholar
• Mieghem, P. V., and E. Cator. 2012. Epidemics in networks with nodal self-infection and the epidemic threshold. Physical Review E 86(1):016116-1–016116-10.
   Web of Science ®Google Scholar
• Mukhopadhyay, A., S. Chatterjee, D. Saha, A. Mahanti, and S.K. Sadhukhan. 2006. e-risk management with insurance: A framework using copula aided bayesian belief networks. In Proceedings of the 39th annual Hawaii international conference on system sciences (HICSS’06), 6, 126.
   Google Scholar
• Nelsen, R. B. 2013. An introduction to copulas, vol. 139. New York: Springer Science & Business Media (New York: IEEE).
   Google Scholar
• Pastor-Satorras, R., C. Castellano, P. V. Mieghem, and A. Vespignani. 2015. Epidemic processes in complex networks. Reviews of Modern Physics 87: 925–979.
   Web of Science ®Google Scholar
• Peng, C., M. Xu, S. Xu, and T. Hu. 2017. Modeling multivariate cybersecurity risks. Journal of Applied Statistics 14: 2534–2563.
   Google Scholar
• Pratt, J. W. 1992. Risk aversion in the small and in the large. In Foundations of insurance economics, ed. P. Diamond and M. Rothschild, 83–98. Springer.
   Google Scholar
• Ross, S. 1996. Stochastic processes. New York: Wiley and Sons.
   Google Scholar
• Schwartz, G. A. and S. S. Sastry. 2014. Cyber-insurance framework for large scale interdependent networks. In Proceedings of the 3rd international conference on high confidence networked systems, 145–154.
   Google Scholar
• Sklar, A. 1959. Fonctions de répartition à n dimensions et leurs marges. Publications de l’Institut de statistique de l’Université de Paris 8: 229–231.
   Google Scholar
• Xu, M., G. Da, and S. Xu. 2015. Cyber epidemic models with dependences. Internet Mathematics 11: 62–92.
   Web of Science ®Google Scholar
• Xu, M., and S. Xu. 2012. An extended stochastic model for quantitative security analysis of networked systems. Internet Mathematics 8: 288–320.
   Google Scholar
• Yang, Z., and J. Lui. 2014. Security adoption and influence of cyber-insurance markets in heterogeneous networks. Performance Evaluation 74: 1–17.
   Web of Science ®Google Scholar
• Zhang, C., S. Zhou, and B. M. Chain. 2015. Hybrid epidemics: A case study on computer worm Conficker. PloS ONE 10(5): e0127478.
   PubMed Web of Science ®Google Scholar