Improving security behavior through better security message comprehension: FMRI and eye-tracking insights

Abstract

Security warnings are critical to help users make contextual security decisions. Unfortunately, users find these warnings hard to understand, and they routinely expose themselves to unintended risks as a result. Although it is straightforward to determine when users fail to understand a warning, it is more difficult to pinpoint why this happens. The goal of this research is to use eye tracking and fMRI to step through the building blocks of comprehension—attention, semantics, syntax, and pragmatics—for SSL and other common security warnings. Through this process, we will identify ways to design security warnings to be more easily understood.