Integrated Threat Intelligence Automation and Simulation Models for Next Generation Cyber Defense

The evolution of cyber threats has rendered traditional defense mechanisms increasingly insufficient, particularly within complex enterprise and critical infrastructure environments. This paper presents an integrated framework combining threat intelligence automation with advanced simulation models to enhance predictive capabilities, optimize resource allocation, and support proactive defense strategies. The framework leverages automated threat data collection, normalization, and correlation across multiple intelligence sources, integrating these inputs into simulation environments that model adversary behaviors and potential attack vectors. By incorporating predictive analytics, machine learning, and dynamic scenario generation, the framework provides actionable insights for security teams and executive decision-makers, enabling anticipatory risk mitigation and operational resilience. Evaluation through simulated attack scenarios demonstrates improvements in detection speed, response coordination, and risk prioritization, highlighting the potential for substantial reductions in exposure to advanced persistent threats. This approach represents a critical step toward next-generation cyber defense, emphasizing automation, intelligence integration, and scenario-based planning to maintain enterprise security in the face of rapidly evolving threats.