Understanding user identification in virtual reality through behavioral biometrics and the efect of body normalization

Abstract

Virtual Reality (VR) is becoming increasingly popular both in the entertainment and professional domains. Behavioral biometrics have recently been investigated as a means to continuously and implicitly identify users in VR. Applications in VR can specifcally beneft from this, for example, to adapt virtual environments and user interfaces as well as to authenticate users. In this work, we conduct a lab study (N = 16) to explore how accurately users can be identifed during two task-driven scenarios based on their spatial movement. We show that an identifcation accuracy of up to 90% is possible across sessions recorded on diferent days. Moreover, we investigate the role of users' physiology in behavioral biometrics by virtually altering and normalizing their body proportions. We fnd that body normalization in general increases the identifcation rate, in some cases by up to 38%; hence, it improves the performance of identifcation systems.