Psychological Profiling in Cybersecurity: A Look at LLMs and Psycholinguistic Features
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.
Keywords
Cite
@article{arxiv.2406.18783,
title = {Psychological Profiling in Cybersecurity: A Look at LLMs and Psycholinguistic Features},
author = {Jean Marie Tshimula and D'Jeff K. Nkashama and Jean Tshibangu Muabila and René Manassé Galekwa and Hugues Kanda and Maximilien V. Dialufuma and Mbuyi Mukendi Didier and Kalonji Kalala and Serge Mundele and Patience Kinshie Lenye and Tighana Wenge Basele and Aristarque Ilunga and Christian N. Mayemba and Nathanaël M. Kasoro and Selain K. Kasereka and Hardy Mikese and Pierre-Martin Tardif and Marc Frappier and Froduald Kabanza and Belkacem Chikhaoui and Shengrui Wang and Ali Mulenda Sumbu and Xavier Ndona and Raoul Kienge-Kienge Intudi},
journal= {arXiv preprint arXiv:2406.18783},
year = {2024}
}