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Olga A. Zielinska, Allaire K. Welk, Emerson Murphy-Hill, Christopher B. Mayhorn.  2016.  A temporal analysis of persuasion principles in phishing emails. Human Factors and Ergonomics Society 60th Annual Meeting.

Eight hundred eighty-seven phishing emails from Arizona State University, Brown University, and Cornell University were assessed by two reviewers for Cialdini’s six principles of persuasion: authority, social proof, liking/similarity, commitment/consistency, scarcity, and reciprocation. A correlational analysis of email characteristics by year revealed that the persuasion principles of commitment/consistency and scarcity have increased over time, while the principles of reciprocation and social proof have decreased over time. Authority and liking/similarity revealed mixed results with certain characteristics increasing and others decreasing. Results from this study can inform user training of phishing emails and help cybersecurity software to become more effective. 

Olga Zielinska, Allaire Welk, Christopher B. Mayhorn, Emerson Murphy-Hill.  2015.  Exploring expert and novice mental models of phishing. HotSoS: Symposium and Bootcamp on the Science of Security.

Experience influences actions people take in protecting themselves against phishing. One way to measure experience is through mental models. Mental models are internal representations of a concept or system that develop with experience. By rating pairs of concepts on the strength of their relationship, networks can be created through Pathfinder, showing an in-depth analysis of how information is organized. Researchers had novice and expert computer users rate three sets of terms related to phishing. The terms were divided into three categories: prevention of phishing, trends and characteristics of phishing attacks, and the consequences of phishing. Results indicated that expert mental models were more complex with more links between concepts. Specifically, experts had sixteen, thirteen, and fifteen links in the networks describing the prevention, trends, and consequences of phishing, respectively; however, novices only had eleven, nine, and nine links in the networks describing prevention, trends, and consequences of phishing, respectively. These preliminary results provide quantifiable network displays of mental models of novices and experts that cannot be seen through interviews. This information could provide a basis for future research on how mental models could be used to determine phishing vulnerability and the effectiveness of phishing training.