Virtual reality (VR) and "metaverse" systems have recently seen a resurgence in interest and investment as major technology companies continue to enter the space. However, recent studies have demonstrated that the motion tracking "telemetry" data used by nearly all VR applications is as uniquely identifiable as a fingerprint scan, raising significant privacy concerns surrounding metaverse technologies. Although previous attempts have been made to anonymize VR motion data, we present in this paper a state-of-the-art VR identification model that can convincingly bypass known defensive countermeasures. We then propose a new "deep motion masking" approach that scalably facilitates the real-time anonymization of VR telemetry data. Through a large-scale user study (N=182), we demonstrate that our method is significantly more usable and private than existing VR anonymity systems.

翻译：虚拟现实（VR）与“元宇宙”系统近期因科技巨头持续布局而再度引发投资热潮与关注。然而最新研究表明，几乎所有VR应用所采用的运动追踪“遥测”数据具有与指纹扫描同等独特的可识别性，这引发了围绕元宇宙技术的重大隐私担忧。尽管已有研究尝试对VR运动数据进行匿名化处理，但本文提出了一种可绕过现有防御机制的最新VR身份识别模型。我们进而提出新型“深度运动遮蔽”方法，该方案能够可扩展地实现VR遥测数据的实时匿名化。通过大规模用户研究（N=182），我们证明了该方法在可用性与隐私保护方面显著优于现有VR匿名系统。