Enhancing cybersecurity curricula through Dark Web education with AI-based hands-on labs

As cybersecurity threats evolve, adversaries increasingly utilize anonymizing technologies like the Dark Web, creating an urgent need to align cybersecurity education with emerging realities. Current curricula reveal significant knowledge gaps, leaving graduates ill-prepared for roles in threat intelligence and digital forensics. This paper presents a novel pedagogical framework that integrates structured Dark Web instruction supported by AI-driven, hands-on laboratory activities. Using a mixed-methods approach, the study surveyed 85 undergraduate students pre-implementation to assess baseline knowledge and evaluated 75 students post-pilot. Initial assessments revealed substantial deficits, with 93.5% of students reporting low confidence in their understanding of Dark Web technologies. Following the pilot, results demonstrated significant improvements in student engagement, conceptual understanding, and satisfaction. The proposed framework incorporates legal, ethical, and technical safeguards to ensure responsible instruction while demonstrating the potential of AI to support scalable, sound education in emerging threat domains.