User Identification in Virtual Reality through Behavioral Biometrics and the Influence of Colocated Interactions

Behavioral Biometrics in Virtual Reality (VR) allow for implicit user identification, as the head- and hand-movements that can be captured from the head-mounted display and the controllers are highly descriptive of the user’s true identity. Such body movements have been explored in the past; however, to date, it is unclear how they perform in settings where more than one person interacts in a shared virtual environment. In this work, we explored through a user study (N=40) how behavioral biometrics in VR change when one or more persons interact with each other in a shared virtual environment and whether this is influenced by the nature of the interaction itself. We find that user identification is possible with up to 83.38 % by applying deep learning models, and that particularly cooperative interactions between multiple VR users lead to highly identifiable body movements. Our results help in advancing behavioral biometrics for seamless user identification in VR, as a viable alternative to using PINs and passwords.