Psychological Profiling in Cybersecurity: A Look at LLMs and Psycholinguistic Features
This work addresses cybersecurity challenges for professionals by proposing an innovative integration of psychology and AI, though it appears incremental as it builds on existing profiling and LLM methods.
The paper tackles the problem of sophisticated cyber threats by exploring psychological profiling techniques using Large Language Models (LLMs) and psycholinguistic features to analyze textual data for identifying threat actors' traits, aiming to bolster cybersecurity defenses.
The increasing sophistication of cyber threats necessitates innovative approaches to cybersecurity. In this paper, we explore the potential of psychological profiling techniques, particularly focusing on the utilization of Large Language Models (LLMs) and psycholinguistic features. We investigate the intersection of psychology and cybersecurity, discussing how LLMs can be employed to analyze textual data for identifying psychological traits of threat actors. We explore the incorporation of psycholinguistic features, such as linguistic patterns and emotional cues, into cybersecurity frameworks. Our research underscores the importance of integrating psychological perspectives into cybersecurity practices to bolster defense mechanisms against evolving threats.