Department of Information and Computer Science, College of Computer Science and Engineering, University of Ha’il, Ha’il, Saudi Arabia
Email: i.alsedon@uoh.edu.sa (I.M.A.)
Manuscript received March 12, 2024; revised May 8, 2024; accepted June 12, 2024; published August 19, 2024
Abstract—Social engineering attack messages are a constant threat to online services. Numerous scholars have attempted to solve this problem by understanding the interaction between users and social engineering attack messages. Users’ behavior and traits are crucial in making them immune to attacks. Specifically, studies have indicated that the mental process of detection has a tremendous effect on preventing users from becoming victims of attacks. Studies have also suggested that users need to think in a certain way to detect deception. Our study aims to determine the impact of warnings on users’ types of thinking to increase secure behavior. A mixed-method approach is applied (i.e. experiment and open-ended questions) to answer research questions. The results indicate that warnings impact users’ types of thinking and have a significant impact on increasing their protection against attacks. In addition, warnings have the benefit of confirming users’ initial judgment of known (familiar) social engineering attack messages without the need to perform deep thinking to identify deception. Additionally, users employ several methods to validate messages. Warning has an effect on these methods.
Keywords—cybersecurity, information security, social engineering, detection
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Cite: Ibrahim Mohammed Alseadoon, "The Benefit of Warning to Improve Detecting Social Engineering Attack Messages," International Journal of Future Computer and Communication, vol. 13, no. 3, pp. 49-54, 2024.
Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
(CC BY 4.0)
