TeachSecure-CTI: Adaptive Cybersecurity Curriculum Generation Using Threat Dynamics and AI

The rapidly evolving cybersecurity threat landscape exposes a critical flaw in traditional educational programs where static curricula cannot adapt swiftly to novel attack vectors. This creates a significant gap between theoretical knowledge and the practical defensive capabilities needed in the field. To address this, we propose TeachSecure-CTI, a novel framework for adaptive cybersecurity curriculum generation that integrates real-time Cyber Threat Intelligence (CTI) with AI-driven personalization. Our framework employs a layered architecture featuring a CTI ingestion and clustering module, natural language processing for semantic concept extraction, and a reinforcement learning agent for adaptive content sequencing. By dynamically aligning learning materials with both the evolving threat environment and individual learner profiles, TeachSecure-CTI ensures content remains current, relevant, and tailored. A 12-week study with 150 students across three institutions demonstrated that the framework improves learning gains by 34%, significantly exceeding the 12%–21% reported in recent literature. The system achieved 84.8% personalization accuracy, 85.9% recognition accuracy for MITRE ATT&CK tactics, and a 31% faster competency development rate compared to static curricula. These findings have implications beyond academia, extending to workforce development, cyber range training, and certification programs. By bridging the gap between dynamic threats and static educational materials, TeachSecure-CTI offers an empirically validated, scalable solution for cultivating cybersecurity professionals capable of responding to modern threats.