September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
Cybersecurity and Fatigue: Does fatigue from visual contrast impact our ability to correctly classify emails?
Author Affiliations
  • Genna Telschow
    University of Central Florida
  • Mark Neider
    University of Central Florida
Journal of Vision September 2021, Vol.21, 2111. doi:https://doi.org/10.1167/jov.21.9.2111
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      Genna Telschow, Mark Neider; Cybersecurity and Fatigue: Does fatigue from visual contrast impact our ability to correctly classify emails?. Journal of Vision 2021;21(9):2111. doi: https://doi.org/10.1167/jov.21.9.2111.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Email phishing schemes represent a constant threat to personal and organizational security. To combat this threat, it is critical to develop a firm understanding of the factors that affect email classification performance. One such factor might be fatigue. Work performance research shows that fatigue impairs information processing, shortens attention span, and slows reaction times. Studies have demonstrated that elevated screen use can induce fatigue that leads to such impairments (Jeong, 2012; Lin et al., 2008). Specifically, Bhattacharyya et al. (2014) showed that changes in text-background contrast induce fatigue. The current study examined whether fatigue impacts email classification performance. Participants first read a series of text-excerpts on a computer screen and answered comprehension questions, after which they classified 100 emails (4 blocks; 25 emails per block) as either legitimate or non-legitimate (50% legitimate; see Sarno et al., 2020). Additionally, we manipulated the text-background contrast of the initial reading task; the text was either black (high contrast/low-fatigue) or yellow text (low contrast/high-fatigue) on a white background. Somewhat surprisingly, we found that the high-fatigue group had higher accuracy (75.6%) than the low-fatigue group (66.4%; pholm= 0.002). Participants performed better when classifying legitimate emails (p< 0.001). Additionally, the high-fatigue group had higher accuracy (75.3%) for non-legitimate emails than the low-fatigue group (48.7%; pholm< 0.001). No group difference was found for legitimate emails (pholm= 0.285). The low-fatigue group also misclassified non-legitimate emails as legitimate at a higher rate (50.6%) than the high-fatigue group (29.5%; p= 0.005). The data support fatigue’s role in email classification performance, but in an unexpected way. Fatigue improves email classification accuracy, particularly for non-legitimate emails. We speculate that the high-fatigue task required participants to actively focus, which increased stress and boosted performance. It is also possible that the high-fatigue condition made participants more cautious, and subsequently changed participants’ email classification criterion.

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