With the recent explosive growth of interest and investment in virtual reality (VR) and the so-called "metaverse," public attention has rightly shifted toward the unique security and privacy threats that these platforms may pose. While it has long been known that people reveal information about themselves via their motion, the extent to which this makes an individual globally identifiable within virtual reality has not yet been widely understood. In this study, we show that a large number of real VR users (N=55,541) can be uniquely and reliably identified across multiple sessions using just their head and hand motion relative to virtual objects. After training a classification model on 5 minutes of data per person, a user can be uniquely identified amongst the entire pool of 50,000+ with 94.33% accuracy from 100 seconds of motion, and with 73.20% accuracy from just 10 seconds of motion. This work is the first to truly demonstrate the extent to which biomechanics may serve as a unique identifier in VR, on par with widely used biometrics such as facial or fingerprint recognition.
翻译:随着对虚拟现实(VR)和所谓的“元数据”的兴趣和投资的爆炸性增长,公众的注意力正确地转向了这些平台可能带来的独特的安全和隐私威胁。虽然人们早已知道人们通过自己的运动暴露了自己的信息,但人们尚未广泛了解这在多大程度上使个人在虚拟现实中可以在全球范围内识别。在这项研究中,我们表明,许多真实的VR用户(N=55 541)可以在多个会话中利用与虚拟物体有关的头部和手动进行独特和可靠的识别。在对每个人5分钟的数据分类模型进行培训后,可以在整个50 000+的人才库中发现一个用户,其精确度从100秒运动开始为94.33%,而仅从10秒运动中就达到73.20%。这项工作首次真正展示了生物机械在VR中作为独特识别数据的程度,与广泛使用的生物鉴别方法(如脸部或指纹识别)相近。