Personal profile
Personal Statement
My research focuses on the growing threat of phishing within mobile instant messaging (MIM) applications. I investigate how the unique design features and communication dynamics of these platforms both heighten user susceptibility to deception and shape the strategies employed by attackers. By analyzing the interplay between usability, trust cues, and social engineering tactics, my work aims to uncover the mechanisms that make MIM environments particularly vulnerable, while also identifying pathways for more effective detection, prevention, and user protection strategies.
Education/Academic qualification
Master in Science, University of Sussex
22 Sept 2013 → 30 Sept 2014
Award Date: 17 Oct 2014
Bachelor of Science, Brunel University
2010 → 20 Jun 2012
Award Date: 20 Jun 2012
Keywords
- Cybersecurity, usable security, phishing, mobile messaging applications
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Getting users to click: a content analysis of phishers’ tactics and techniques in mobile instant messaging phishing
Ahmad, R., Terzis, S. & Renaud, K., 25 Sept 2024, In: Information and Computer Security. 32, 4, p. 420-435 16 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile6 Link opens in a new tab Citations (Scopus)50 Downloads (Pure) -
Content analysis of persuasion principles in mobile instant message phishing
Ahmad, R., Terzis, S. & Renaud, K., 26 Jul 2023, Human Aspects of Information Security & Assurance: 17th International Symposium on Human Aspects of Information Security & Assurance. Furnell, S. & Clarke, N. (eds.). Cham, Switzerland: Springer, p. 324-336 13 p. (IFIP Advances in Information and Communication Technology; vol. 674).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
3 Link opens in a new tab Citations (Scopus)
Datasets
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Data for: "Getting users to click: a content analysis of phishers’ tactics and techniques in mobile instant messaging phishing"
Ahmad, R. (Creator) & Terzis, S. (Supervisor), University of Strathclyde, 5 Feb 2026
DOI: 10.15129/2a93dde8-f088-4762-ba34-c8215498b697
Dataset