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With the recent explosive growth of interest and investment in virtualreality (VR) and the so-called "metaverse," public attention has rightlyshifted toward the unique security and privacy threats that these platforms maypose. While it has long been known that people reveal information aboutthemselves via their motion, the extent to which this makes an individualglobally identifiable within virtual reality has not yet been widelyunderstood. In this study, we show that a large number of real VR users(N=55,541) can be uniquely and reliably identified across multiple sessionsusing just their head and hand motion relative to virtual objects. Aftertraining a classification model on 5 minutes of data per person, a user can beuniquely identified amongst the entire pool of 50,000+ with 94.33% accuracyfrom 100 seconds of motion, and with 73.20% accuracy from just 10 seconds ofmotion. This work is the first to truly demonstrate the extent to whichbiomechanics may serve as a unique identifier in VR, on par with widely usedbiometrics such as facial or fingerprint recognition.

Unique Identification of 50,000+ Virtual Reality Users from Head & Hand Motion Data