Multimodal Biometric Authentication for VR/AR using EEG and Eye Tracking


Electroencephalogram (EEG) signals can enable an additional non-intrusive input modality especially when paired with a wearable headset (i.e. AR/VR). A great challenge in using EEG data for Brain-Computer Interface (BCI) algorithms is its poor generalization performance across users. Taking advantage of these inter-user differences, we investigate the potential in using this technology for user authentication – similar to facial recognition in smartphones. Additionally, we evaluate this in combination with eye tracking data which is also readily available in such headsets. We develop a biometric authentication systems for each of these systems and for their fusion. We formulate a novel evaluation paradigm using publicly available EEG motor imagery and eye tracking data and demonstrate strong feasibility towards using EEG and eye tracking for authentication.

In Adjunct of the 2019 International Conference on Multimodal Interaction, 2019.