THREAT MODELING FOR SECURITY ARCHITECTS: INTEGRATING GAME THEORY AND RISK ASSESSMENT ALGORITHM

Abstract : In the face of increasingly sophisticated and persistent cyber threats, effective threat modeling has become a foundational aspect of security architecture design. This paper introduces a novel approach to threat modeling that integrates game theory with algorithmic risk assessment, enabling security architects to proactively identify, evaluate, and prioritize threats within complex systems. Traditional threat modeling techniques often rely on static risk matrices or qualitative frameworks, which may lack the dynamism and strategic foresight needed to contend with adaptive adversaries. By contrast, the proposed model leverages game theory to simulate attacker-defender interactions as strategic games, capturing the adversarial nature of cybersecurity and enabling the anticipation of attacker behavior based on rational choice under constraints. Game-theoretic models such as Nash Equilibrium and Stackelberg Games are applied to represent scenarios where attackers and defenders have conflicting goals and asymmetric information. Complementing this, an algorithmic risk assessment component dynamically quantifies risk based on evolving threat intelligence, asset criticality, and vulnerability exploitability, using weighted scoring models and probabilistic inference. The integration of these two frameworks allows for continuous reassessment of the threat landscape and supports decision-making regarding the optimal allocation of defense resources. A prototype tool implementing this hybrid model was tested on enterprise network topologies and critical infrastructure simulations, demonstrating its ability to identify dominant attack paths, recommend countermeasures, and prioritize mitigations based on calculated utility outcomes. Evaluation results show improved accuracy and responsiveness in threat prioritization compared to traditional static models, with measurable benefits in resource optimization and reduced exposure to high-impact threats. Furthermore, the system’s flexibility allows it to adapt to different domains, including cloud architectures, IoT networks, and cyber-physical systems. The paper also discusses practical considerations for implementation, including computational complexity, data requirements, and integration with existing security information and event management (SIEM) platforms. Overall, the integration of game theory and algorithmic risk assessment provides a more strategic and analytical approach to threat modeling, enabling security architects to make informed, context-aware decisions in the design and defense of secure systems. This work contributes to the evolving discipline of proactive cybersecurity engineering, advocating for the use of predictive, mathematically grounded tools that align more closely with the realities of adversarial behavior and risk management in modern digital ecosystems.

Keyword Threat Modeling; Game Theory; Risk Assessment; Cybersecurity Architecture; Adversarial Modeling; Strategic Defense Planning