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Psychological Profiling in Cybersecurity: A Look at LLMs and Psycholinguistic Features

26 June 2024
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
N. Kasoro
S. Kasereka
Hardy Mikese
Pierre Martin Tardif
Marc Frappier
F. Kabanza
Belkacem Chikhaoui
Shengrui Wang
Ali Mulenda Sumbu
Xavier Ndona
Raoul Kienge-Kienge Intudi
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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.

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