Raju, Mehedi H.Friedman, LeeLohr, Dillon J.Komogortsev, Oleg V.2024-03-272024-03-272024-03Mehedi Hasan Raju, Lee Friedman, Dillon J. Lohr, and Oleg V. Komogortsev. 2024. Signal vs Noise in Eye-tracking Data: Biometric Implications and Identity Information Across Frequencies. In 2024 Symposium on Eye Tracking Research and Applications (ETRA ’24), June 4–7, 2024, Glasgow, United Kingdom. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3649902.3653353https://hdl.handle.net/10877/18331Prior research states that frequencies below 75 Hz in eye-tracking data represent the primary eye movement termed “signal” while those above 75 Hz are deemed “noise”. This study examines the biometric significance of this signal-noise distinction and its privacy implications. There are important individual differences in a person’s eye movement, which lead to reliable biometric performance in the “signal” part. Despite minimal eye-movement information in the “noise” recordings, there might be significant individual differences. Our results confirm the “signal” predominantly contains identity-specific information, yet the “noise” also possesses unexpected identity-specific data. This consistency holds for both short-(≈ 20 min) and long-term (≈ 1 year) biometric evaluations. Understanding the location of identity data within the eye movement spectrum is essential for privacy preservation.Text10 pages1 file (.pdf)1 file (.zip)eneye movementbiometricsignalnoiseArticlehttps://doi.org/10.1145/3649902.3653353