No Anonymity in Metaverse: VR User Identification Based on DTW Distance of Head-and-Arms Motions
Koki Miura, Hiroaki Kikuchi · EPiC series in computing · 2025
In recent years, the adoption rate of virtual reality (VR) technology has been on the rise, and the metaverse is attracting attention as a next-generation form of internet usage. VR offers a variety of applications and content, such as education, gaming, and tourism, where users can remain anonymous and behave as fictional characters. However, there is a possibility that individuals in the real world can be identified from motion data that records VR users’ head-and-hands movements in detail, represented in time-series data. Nair and Lieber demonstrated that publicly available replay data from the VR rhythm game "Beat Saber" can identify individuals with over 90% accuracy. Nevertheless, the features that had the greatest impact on identification accuracy were static attributes such as height and arm length. Therefore, in this study, we attempt to identify individuals in VR domain based on dynamic features such as users’ distinctive ways of moving their arms by employing the DTW (Dynamic Time Warping) distance derived from motion data recorded during VR experiences.