{"ID":2841987,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.09846","arxiv_id":"2511.09846","title":"Real-Time Lightweight Gaze Privacy-Preservation Techniques Validated via Offline Gaze-Based Interaction Simulation","abstract":"This study examines the effectiveness of the real-time privacy-preserving techniques through an offline gaze-based interaction simulation framework. Those techniques aim to reduce the amount of identity-related information in eye-tracking data while improving the efficacy of the gaze-based interaction. Although some real-time gaze privatization methods were previously explored, their validation on the large dataset was not conducted. We propose a functional framework that allows to study the efficacy of real-time gaze privatization on an already collected offline dataset. The key metric used to assess the reduction of identity-related information is the identification rate, while improvements in gaze-based interactions are evaluated through signal quality during interaction. Our additional contribution is the employment of an extremely lightweight Kalman filter framework that reduces the amount of identity-related information in the gaze signal and improves gaze-based interaction performance.","short_abstract":"This study examines the effectiveness of the real-time privacy-preserving techniques through an offline gaze-based interaction simulation framework. Those techniques aim to reduce the amount of identity-related information in eye-tracking data while improving the efficacy of the gaze-based interaction. Although some re...","url_abs":"https://arxiv.org/abs/2511.09846","url_pdf":"https://arxiv.org/pdf/2511.09846v1","authors":"[\"Mehedi Hasan Raju\",\"Oleg V. Komogortsev\"]","published":"2025-11-13T01:01:34Z","proceeding":"cs.HC","tasks":"[\"cs.HC\",\"cs.CR\"]","methods":"[]","has_code":false}