Additionally, we present empirical evidence of Kalεido's effectiveness in thwarting real-world attacks on eye-tracking data. Our user study shows that the users enjoy a satisfactory level of utility from Kalεido. These measurements are carried out by an eye tracker, that records the position of the eyes and the movements they make. We conduct a comprehensive user study and trace-based analysis to evaluate Kalεido. Eye tracking refers to the process of measuring where we look, also known as our point of gaze. Kalεido acts as an intermediary protection layer in the software stack of eye-tracking systems. In this paper, we propose Kalεido, an eye-tracking data processing system that (1) provides a formal privacy guarantee, (2) integrates seamlessly with existing eye-tracking ecosystems, and (3) operates in real-time. Prior approaches to protecting eye-tracking data suffer from two major drawbacks: they are either incompatible with the current eye-tracking ecosystem or provide no formal privacy guarantee. However, eye gaze data is a rich source of sensitive information that can reveal an individual's physiological and psychological traits. Ranging from mobiles to high-end mixed reality headsets, a wide spectrum of interactive systems now employs eye-tracking. Recent advances in sensing and computing technologies have led to the rise of eye-tracking platforms.
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