Multitasking and Monetary Incentive in a Realistic Phishing Study
Haoruo Zhang, Shirish Singh, Xiang‐Yang Li, Anton T. Dahbura, Meng Xie · Electronic workshops in computing · 2018
This paper introduces an empirical study focusing on task settings similar to those in the real-world that captures user behavioral information of fine granularity. In online experiments, participants recruited from the Mechanical Turk human subject pool sorted legitimate and phishing emails. Subgroups of these remote users performed a secondary question-answering task and/or were incentivized by a monetary reward based on email sorting accuracy. This web-based framework automates a complete process from the informed consent to a post-study questionnaire, which can be scaled up to a large number of human subjects. In the preliminary result analysis, the monetary incentive can positively affect users’ behavior and performance, but not in a straightforward manner. Multitasking, on the other hand, has a negative effect on users’ ability to correctly classify emails.