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The Effects of Cue Utilization and Cognitive Load in the Detection of Phishing Emails

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Financial Cryptography and Data Security (FC 2020)

Abstract

Phishing emails represent a major threat to online information security. While the prevailing research is focused on users’ susceptibility, few studies have considered the decision making strategies that account for skilled detection. One relevant facet of decision making is cue utilization, where users retrieve feature-event associations stored in long-term memory. High degrees of cue utilization help reduce the demands placed on working memory (i.e., cognitive load), and invariably improve decision performance (i.e., the information-reduction hypothesis in expert performance). The current study explored the effect of cue utilization and cognitive load when detecting phishing emails. A total of 50 undergraduate students completed: (1) a rail control task and; (2) a phishing detection task. A cue utilization assessment battery (EXPERTise 2.0) then classified participants with either higher or lower cue utilization. As expected, higher cue utilization was associated with a greater likelihood of detecting phishing emails. However, variation in cognitive load had no effect on phishing detection, nor was there an interaction between cue utilization and cognitive load. These findings have implications for our understanding of cognitive mechanisms that underpin the detection of phishing emails and the role of factors beyond the information-reduction hypothesis.

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Correspondence to Ben W. Morrison .

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Nasser, G., Morrison, B.W., Bayl-Smith, P., Taib, R., Gayed, M., Wiggins, M.W. (2020). The Effects of Cue Utilization and Cognitive Load in the Detection of Phishing Emails. In: Bernhard, M., et al. Financial Cryptography and Data Security. FC 2020. Lecture Notes in Computer Science(), vol 12063. Springer, Cham. https://doi.org/10.1007/978-3-030-54455-3_4

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  • DOI: https://doi.org/10.1007/978-3-030-54455-3_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-54454-6

  • Online ISBN: 978-3-030-54455-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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