Eye-tracking sensors track where a user looks and are being increasingly integrated into mixed-reality devices. Although critical applications are being enabled, there are significant possibilities for violating user security and privacy expectations. There is an appreciable risk of unique user identification from eye-tracking camera images and the resulting eye movement data. Biometric identification would allow an app to connect a user’s personal ID with their work ID without needing their consent, for example. Solutions were explored to address concerns related to the leaking of biometric features through eye-tracking data streams. Privacy mechanisms are introduced to reduce the risk of biometric recognition while still enabling applications of eye-tracking data streams. Gaze data streams can thus be made private while still allowing for applications key to the future of mixed-reality technology, such as animating virtual avatars or prediction models necessary for foveated rendering.
Dr. Brendan David-John (he/him/his) is an Assistant Professor of Computer Science at Virginia Tech. Brendan was the first Native male to graduate with a doctorate in Computer Science from the University of Florida in 2022, and received his BS and MS from the Rochester Institute of Technology in 2017. He is from Salamanca NY, which is located on the Allegany reservation of the Seneca Nation of Indians. His personal goals include increasing the representation of Native Americans in STEM and higher education, specifically in computing. He is a proud member of the American Indian Science & Engineering Society and has been a Sequoyah Fellow since 2013. His research interests include virtual reality and eye tracking, with a primary focus on privacy and security for the future of virtual and mixed reality.