A Stochastic Assessment of Service Loss due to Cyber Vulnerabilities of Power Network Infrastructure: A Case Study of Puerto Rico

Power network models often incorporate risks from extreme weather events to inform public policy, yet lack the consideration of emerging risks such as cyberattacks. This is in part due to the difficulty in modeling the increasing yet not well-understood risks related to cyber-attacks. In this work, we propose a stochastic approach to statistically gauge the service level loss from a cyberattack on a community's power network and other critical infrastructures. This simulation approach allows for component level analysis of cyberattack implications using power loss as a reflective manifestation of socioeconomic impacts. The developed methodology is valuable for policy-makers who must allocate resources to mitigate risks, especially cybersecurity risks, of infrastructure failure and stakeholders who are financially invested in a community's power network. Furthermore, we illustrate the utility of our approach by simulating cyberattack scenarios across components of the power generation and transmission system in the context of Puerto Rico. Our methodology stands apart from other simulated disaster-related literature in that (i) it captures the societal impact of an actual cyberattack, and (ii) it is adaptive for new infrastructural changes that stakeholders may implement.