"New Research Suggests That Privacy in the Metaverse Might Be Impossible"

A new study from the University of California, Berkeley, suggests that privacy in the metaverse may be unattainable without the development of novel user protections. The recently published study, led by graduate researcher Vivek Nair and conducted at the Center for Responsible Decentralized Intelligence (RDI), included the largest data set of user interactions in Virtual Reality (VR) ever examined for privacy risks. Surprisingly, only a small amount of data is required to uniquely identify a person in the metaverse, removing the possibility of real anonymity in virtual environments. The new Berkeley study, "Unique Identification of 50,000-plus Virtual Reality Users from Head and Hand Motion Data," analyzed more than 2.5 million fully anonymized VR data recordings from over 50,000 players of the popular Beat Saber app and found that individual users could be uniquely identified with an accuracy of more than 94 percent using only 100 seconds of motion data. With just two seconds of motion data, half of all users could be uniquely identified. This level of accuracy required advanced Artificial Intelligence (AI) methods, but the data used was relatively scarce, with only three spatial points tracked for each user over time. When a user puts on a mixed reality headset, grips the two standard hand controllers, and interacts with a virtual or augmented world, they leave a trail of digital fingerprints that can be used to uniquely identify them. This article continues to discuss the study on the unique identification of VR users. 

VB reports "New Research Suggests That Privacy in the Metaverse Might Be Impossible"