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Abstract

Cybersecurity is the practice of protecting systems, networks, and data from digital attacks. Cy-<br>berpsychology (CPSY) is defned as the use of psychology to enhance cybersecurity applications.<br>Since the early 2010s, the evolution of Artifcial Intelligence (AI) has increasingly integrated with<br>CPSY, leveraging advanced data analysis to decode the distinct personality traits and behavioral<br>patterns of victims, attackers, and defenders. In this systematic literature review (SLR), we carefully<br>analyze 34 collected research studies of AI usage in cyberpsychology (AI-CPSY) using the preferred<br>reporting items for systematic reviews and meta-analyses (PRISMA) methodology. The review<br>presents a comprehensive taxonomy of the cyber-security applications, the AI methodologies used,<br>and the psychological concepts employed across the studies . We sort the research studies into<br>four cybersecurity applications: Anomaly Detection (AD), Vulnerability Risk Prediction (VRP),<br>Security Awareness Training (SAT), and Authentication/Identity Verifcation (AIV). Within each<br>application area, studies are further sorted according to the AI method used including machine<br>learning (ML), deep learning (DL), natural language processing (NLP), and reinforcement learning<br>(RL). Furthermore, the review identifes the most commonly utilized psychological concepts, quantify<br>the datasets used in the feld, and present their current implementation and deployment status. At<br>last, it detect research gaps, present open challenges, and deduce the trending and most efective and<br>emerging methodologies used across the AI-CPSY landscape.