Machine Learning and Deep Learning Techniques in Countering Cyberterrorism

In recent years, artificial intelligence (AI) has emerged as a critical tool in automating data detection and acquisition processes, significantly contributing to bolstering national security efforts. The integration of human-like attributes into machines enables AI to address challenges akin to human cognitive faculties, thus becoming a preferred approach in decision-making. Notably, AI has gained substantial traction in identifying criminal and radical activities online. Within the domain of AI, machine learning (ML) plays a pivotal role in automating data detection, particularly in detecting radical behaviours online. However, despite its potential, ML encounters challenges arising from the complexity and diversity of cyber-attacks, which might impact the accuracy and applicability of the algorithms. The primary aim of this chapter is to delve into the technical dimensions of AI concerning cyber security and cyber terrorism. Particularly, the chapter focuses on investigating the pivotal role ML and deep learning (DL) play in identifying extremist content and activities on online platforms. Through a comprehensive examination of these two domains, the chapter endeavours to illuminate the potential pathways through which AI can bolster cyber security measures and effectively combat cyber terrorism.