Beyond Gaze Points: Augmenting Eye Movement with Brainwave Data for Multimodal User Authentication in Extended Reality

TL;DR

This paper presents a multimodal biometric authentication system for XR that combines eye movements and brainwave data, achieving high accuracy and seamless user experience with consumer-grade sensors.

Contribution

It introduces a novel multimodal biometric system using eye and brain data for XR authentication, outperforming existing unimodal and biometric methods.

Findings

Achieves an EER of 0.29%, outperforming individual modalities.

Supports seamless authentication via visual stimuli.

Outperforms state-of-the-art biometric authentication methods.

Abstract

Extended Reality (XR) technologies are becoming integral to daily life. However, password-based authentication in XR disrupts immersion due to poor usability, as entering credentials with XR controllers is cumbersome and error-prone. This leads users to choose weaker passwords, compromising security. To improve both usability and security, we introduce a multimodal biometric authentication system that combines eye movements and brainwave patterns using consumer-grade sensors that can be integrated into XR devices. Our prototype, developed and evaluated with 30 participants, achieves an Equal Error Rate (EER) of 0.29%, outperforming eye movement (1.82%) and brainwave (4.92%) modalities alone, as well as state-of-the-art biometric alternatives (EERs between 2.5% and 7%). Furthermore, this system enables seamless authentication through visual stimuli without complex interaction.