Foundational Methods for Cyber Risk Quantification in Complex Digital Environments

Abstract

The digital environment of the business world is marked by digital ecosystems, which exhibit structural interdependencies, therefore, imposing an impact on the cyber exposure profile. Distributed systems, microservices systems, federated identity systems, and third-party systems result in tightly coupled systems where a nonlinear behavior of cyber compromise events occurs. The systemic risks of cyber exposure are likely to be significantly underestimated through the traditional methods of quantifying cyber risks that are usually linear aggregation of losses incurred by independent assets. The research formulates a quantitative model of cyber risk measurement that takes into consideration the challenges of digital ecosystems. This framework combines digital asset graph modeling, dependency weight estimation, threat vector stratification, vulnerability cluster evaluation, propagation-weighted financial loss calculation, and stochastic simulation. This framework embeds the effects of structural interdependencies into probabilistic modeling, which characterizes cyber exposure as a financially weighted, dynamically influenced distribution. An anonymized financial enterprise case demonstrates the benefits of the framework, which displays increased expected and tail losses with the inclusion of structural dependencies. This framework presents a foundational model for cyber risk quantification that can be scaled for financial evaluation for enterprise cyber governance.