Psychological Profiling in Cybersecurity: A Look at LLMs and Psycholinguistic Features
Jean Marie Tshimula, D'Jeff K. Nkashama, Jean Tshibangu Muabila, René Manassé Galekwa, Hugues Kanda, Maximilien V. Dialufuma, Mbuyi Mukendi Didier, Kalonji Kalala, Serge Mundele, Patience Kinshie Lenye, Tighana Wenge Basele, Aristarque Ilunga, Christian N. Mayemba, Nathanaël M. Kasoro, Selain K. Kasereka, Hardy Mikese, Pierre-Martin Tardif, Marc Frappier, Froduald Kabanza, Belkacem Chikhaoui, Shengrui Wang, Ali Mulenda Sumbu, Xavier Ndona, Raoul Kienge-Kienge Intudi
TL;DR
Problem addressed: how psychological profiling can inform cybersecurity defense in the age of capable LLMs. Approach: synthesize literature on LLM-based profiling and psycholinguistic cues, including LIWC and Big Five concepts, and discuss benefits, challenges, and ethics. Contributions: guidance on applying LLMs and psycholinguistic features for threat detection, along with a framework for ethical deployment and future research directions. Significance: offers a path to deeper behavioral intelligence in cybersecurity and underscores governance needs for responsible use.
Abstract
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.