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Psychological, Situational, and Demographic Predictors of Susceptibility to Ransomware Social-Engineering Lures: A Survey Study

Author

Listed:
  • Aminu Muhammad Auwal

    (Faculty of Natural Sciences, University of Jos, Plateau State, Nigeria)

  • Sulaiman Shehu

    (Department of Software Engineering, Bayero University, Kano, Kano State, Nigeria)

Abstract

Background: Ransomware infections commonly begin through social engineering, yet organizational defenses focus primarily on malware and generic awareness training. Objective: To assess whether Big Five personality traits, digital self-efficacy, workplace time pressure, age, and prior security training predict susceptibility to ransomware-related social engineering lures; determine the independent effect of time pressure; and evaluate the potential protective effect of training. Methods: A cross-sectional study included 612 working adults in Nigeria recruited through a commercial online panel. Participants completed the BFI-44, a 12-item digital self-efficacy scale, four workplace time-pressure items, and 12 simulated ransomware scenarios. Binary logistic regression modeled susceptibility, defined as classifying four or more lures as legitimate. Results: High conscientiousness (OR=0.61; 95% CI: 0.49-0.76; p

Suggested Citation

  • Aminu Muhammad Auwal & Sulaiman Shehu, 2026. "Psychological, Situational, and Demographic Predictors of Susceptibility to Ransomware Social-Engineering Lures: A Survey Study," NeuroData, Editorial JOGB, vol. 3, pages 305-305, January.
    • Handle: RePEc:cxn:neurod:v:3:y:2026:id:305
    DOI: 10.63688/neurodata2026305
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