Automated Policy Enforcement and Vulnerability Prediction via Multi-Modal Knowledge Fusion and Adaptive Game Theory (MPVF-AGT)

**Abstract:** This paper presents the Automated Policy Enforcement and Vulnerability Prediction via Multi-Modal Knowledge Fusion and Adaptive Game Theory (MPVF-AGT) framework, a novel approach to proactively safeguarding cyberspace by dynamically enforcing security policies and anticipating emerging vulnerabilities. Combining advanced natural language processing (NLP), knowledge graph (KG) construction, and adaptive game theory (AGT), MPVF-AGT enhances existing cybersecurity policy management systems by generating actionable threat intelligence and enabling automated policy adjustments against evolving attack landscapes. This system is immediately commercializable for enterprise cybersecurity, government agencies, and critical infrastructure providers, offering a significant advantage in reducing response times and minimizing potential breaches.