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Psychological Profiling in Cybersecurity: A Look at LLMs and Psycholinguistic Features
Groupe de Recherche de Prospection et Valorisation des Données (Greprovad), Canada; University of Kinshasa, Republic Congo; Université de Sherbrooke, Canada.
Groupe de Recherche de Prospection et Valorisation des Données (Greprovad), Canada; Université de Sherbrooke, Canada.
Données (Greprovad), Canada; Université Paris-Saclay, France.
Groupe de Recherche de Prospection et Valorisation des Données (Greprovad), Canada; University of Kinshasa, Republic Congo; University of Klagenfurt, Austria .
Show others and affiliations
2025 (English)In: Proceedings-Web Information Systems Engineering – WISE 2024 PhD Symposium, Demos and Workshop / [ed] Mahmoud Barhamgi, Hua Wang, Xin Wang, Esma Aïmeur, Michael Mrissa, Belkacem Chikhaoui, Khouloud Boukadi, Rima Grati, Zakaria Maamar, Springer Science and Business Media Deutschland GmbH , 2025, Vol. 15463 LNCS, p. 378-393Conference paper, Published paper (Refereed)
Abstract [en]

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. 

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2025. Vol. 15463 LNCS, p. 378-393
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 15463 LNCS
Keywords [en]
Cyber attacks; Cyber security; Cyber threats; Defence mechanisms; Innovative approaches; Language model; Large language model; Linguistic patterns; Psycholinguistic feature; Psychological profiling; Textual data; Psychoacoustic
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:kau:diva-104640DOI: 10.1007/978-981-96-1483-7_31ISI: 001547183700031Scopus ID: 2-s2.0-105000369250ISBN: 978-981-96-1482-0 (print)ISBN: 978-981-96-1483-7 (electronic)OAI: oai:DiVA.org:kau-104640DiVA, id: diva2:1963861
Conference
WEB-for-GOOD 2024, AIWDA 2024, SWIFT-AG 2024, and Demos, Doha, Qatar, December 2-5, 2024.
Available from: 2025-06-04 Created: 2025-06-04 Last updated: 2026-02-12Bibliographically approved

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