SoK: Data Privacy in Virtual Reality
Authors: Gonzalo Munilla Garrido (TUM), Vivek Nair (UC Berkeley), Dawn Song (UC Berkeley)
Volume: 2024
Issue: 1
Pages: 21–40
DOI: https://doi.org/10.56553/popets-2024-0003
Abstract: The adoption of virtual reality (VR) technologies has rapidly gained momentum in recent years as companies around the world begin to position the so-called ''metaverse'' as the next major medium for accessing and interacting with the internet. While consumers have become accustomed to a degree of data harvesting on the web, the real-time nature of data sharing in the metaverse indicates that privacy concerns are likely to be even more prevalent in the new ''Web 3.0.'' Research into VR privacy has demonstrated that a plethora of sensitive personal information is observable by various would-be adversaries from just a few minutes of telemetry data. On the other hand, we have yet to see VR parallels for many privacy-preserving tools aimed at mitigating threats on conventional platforms. This paper aims to systematize knowledge on the landscape of VR privacy threats and countermeasures by proposing a comprehensive taxonomy of data attributes, protections, and adversaries based on the study of 74 collected publications. We complement our qualitative discussion with a statistical analysis of the risk associated with various data sources inherent to VR in consideration of the known attacks and defenses. By focusing on highlighting the clear outstanding opportunities, we hope to motivate and guide further research into this increasingly important field.
Keywords: Augmented reality, security, threat model, defense model, attacks, incognito mode
Copyright in PoPETs articles are held by their authors. This article is published under a Creative Commons Attribution 4.0 license.
