AI and Network Security Curricula: Minding the Gap

The ongoing expansion of the digital landscape has led to a growing convergence between the fields of artificial intelligence (AI) and network security. This has necessitated the need for universities to incorporate AI into their network security curriculum. Although traditional network security courses are considered crucial, they lack the agility to address constantly evolving threats. AI offers a transformative solution to such difficulties with its predictive analytics, real-time intrusion detection, and adaptive learning capabilities. This study highlights the importance of incorporating AI into network security curricula at the undergraduate level. A modification to the curriculum is proposed, wherein AI themes are integrated into network security courses and labs. The proposed curricula include understanding theoretical AI concepts and designing AI-augmented hands-on laboratories. The pedagogy emphasizes the tools, and frameworks that facilitate the construction of AI models for intrusion detection, malware analysis, and network analytics. This plays a significant importance in providing a simulated environment for students to engage with AI tools and methods to address authentic cyber threats.