Providing Privacy for Eye-Tracking Data With Applications in XR

Eye tracking is emerging as a foundational sensing modality for extended reality (XR), enabling efficient rendering, natural interaction, and behavior-driven adaptive systems. However, eye-tracking data introduce significant privacy risks, including the potential leakage of biometric identity and sensitive behavioral information. This article summarizes the impact of my dissertation, which develops privacy-preserving techniques across the eye-tracking pipeline (David-John et al., 2022). This includes protecting biometric data at the sensor level, within real-time gaze data streams, and applying formal privacy guarantees to datasets. The results demonstrate that privacy and functionality are not mutually exclusive, and that privacy-by-design approaches can shape the future of XR systems and platforms.