Dynamic Warnings: An Eye Gaze-Based Approach

Mini Zeng, Feng Zhu and Sandra Carpenter
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Mini Zeng: Jacksonville University, USA
Feng Zhu: University of Alabama in Huntsville, USA
Sandra Carpenter: University of Alabama in Huntsville, USA

International Journal of Information Security and Privacy (IJISP), 2022, vol. 16, issue 1, 1-28

Abstract: People often unnecessarily disclose identity information online and puts their privacy at risk. Computer warnings mitigate needless identity disclosure. People, however, often click the OK button without reading warning messages. We utilize eye gaze information to provide dynamic warnings. The dynamic warnings are designed to display just-in-time and then fade out after users read them. They are shown right next to the location where users look. We built a restaurant reservation app to evaluate our dynamic warning system. We conducted an experiment with follow-up surveys. The results showed that our dynamic warnings reduced unnecessary identity disclosure and that they were around 5 times more effective than a Windows warning with a close button. We also found that the longer users’ eyes registered on dynamic warning, the less likely users were to provide their identify information in the dynamic warning condition experiment.

Date: 2022
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