The roles of phishing knowledge, cue utilization, and decision styles in phishing email detection.

Cue utilization Cybersecurity Information processing Phishing Visual search

Journal

Applied ergonomics
ISSN: 1872-9126
Titre abrégé: Appl Ergon
Pays: England
ID NLM: 0261412

Informations de publication

Date de publication:
09 May 2024
Historique:
received: 26 10 2023
revised: 22 04 2024
accepted: 04 05 2024
medline: 11 5 2024
pubmed: 11 5 2024
entrez: 10 5 2024
Statut: aheadofprint

Résumé

This study investigated the roles of phishing knowledge, cue utilization, and decision styles in contributing to phishing email detection. Participants (N = 145) completed an online email sorting task, and measures of phishing knowledge, email decision styles, cue utilization, and email security awareness. Cue utilization was the only factor that uniquely predicted the capacity to discriminate phishing from genuine emails. Phishing knowledge was associated with greater phishing detection and a bias towards classifying all emails as phishing. A preference for intuitive decision making predicted lower detection of phishing emails, driven by a greater tendency to classify emails as genuine. These findings support the proposition that cue utilization is a distinct cognitive process that enables expert performance. The outcomes indicate that, in addition to increasing phishing knowledge and developing safe behavioral patterns, anti-phishing training needs to provide opportunities for trainees to develop meaningful cue associations.

Identifiants

pubmed: 38729025
pii: S0003-6870(24)00086-3
doi: 10.1016/j.apergo.2024.104309
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104309

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Daniel Sturman (D)

The University of Adelaide, SA, Australia. Electronic address: daniel.sturman@adelaide.edu.au.

Elliot A Bell (EA)

The University of Adelaide, SA, Australia.

Jaime C Auton (JC)

The University of Adelaide, SA, Australia.

Georgia R Breakey (GR)

The University of Adelaide, SA, Australia.

Mark W Wiggins (MW)

Macquarie University, NSW, Australia.

Classifications MeSH