Framework for Cyber Risk Loss Distribution of Hospital Infrastructure: Bond Percolation on Mixed Random Graphs Approach

Networks like those of healthcare infrastructure have been a primary target of cyberattacks for over a decade. From just a single cyberattack, a healthcare facility would expect to see millions of dollars in losses from legal fines, business interruption, and malpractice lawsuits. As more medical devices become interconnected, more cyber vulnerabilities emerge resulting in more potential exploitations that may disrupt patient care and result in catastrophic financial losses. In this paper, we propose a bidirectional structural model of an aggregate loss distribution for cyber risk on a mixed random network. Our framework accounts for the documented cyber vulnerabilities of a hospital’s trusted internal network of its major medical assets. Up to our knowledge, there exists no other models of an aggregate loss distribution for cyber risk in this setting. We contextualize the problem in the probabilistic graph-theoretical framework using a percolation model and combinatorial techniques to compute the mean and variance of the loss distribution for a mixed random network that can be useful for insurers working on the implementation of cyber insurance policies, healthcare administrators, and cyber professionals.