Agent based modeling of third-party enterprise cybersecurity

This thesis explores the use of Agent-Based Models (ABMs) to simulate cybersecurity risks within third-party relationships, an increasingly critical area in modern enterprise environments. As businesses rely more on external vendors for essential functions, their cybersecurity exposure grows, often introducing complex and unpredictable risks. The study first provides a comprehensive review of Third-Party Cyber Risk Management (TPCRM), identifying key challenges organizations face in mitigating cybersecurity threats originating from third parties. These challenges include high complexity, lack of visibility and control, and resource constraints. The study also identified recommendations and best practices for TPCRM programs including conducting due diligence, continuous monitoring, and having strong contracts. Using the findings from this review, the thesis develops an ABM to simulate real-world scenarios involving third-party cyber risks. The model, designed in the NetLogo platform, is created using the challenges and best practices identified in the literature. By representing third-party companies, cyber attackers, and the primary organization as agents, the model explores how these entities interact and how effective risk management strategies can prevent breaches or minimize their impact. The study highlights how organizations can balance prevention and recovery costs in TPCRM. The results provide practical insights into optimizing cybersecurity measures for enterprises of varying sizes and complexities, offering a tool to enhance resilience against growing cyber threats.