C. Emre Koksal

The paper proposes a dynamic queueing framework that estimates an organization's cyber resources and attack surface dynamics by analyzing the timestamps of vulnerabilities and fixes, achieving high accuracy in resource prediction.

The paper introduces a queueing-theoretic framework to model dynamic cyber-attack surfaces, developing an adaptive reinforcement learning defense policy that significantly reduces active vulnerabilities and quantifies cumulative exposure risk.