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 68 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.
翻译:近些年来,随着世界各地公司开始将所谓的“元数据”作为获取和与互联网互动的下一个主要媒介,虚拟现实技术的采用迅速获得势头。虽然消费者已经习惯在网上收集某种程度的数据,但元数据共享的实时性质表明,在新的“Web 3.0”中,隐私问题很可能更加普遍。对VR隐私的研究表明,各种潜在对手从几分钟遥测数据中可以看到大量敏感个人信息。另一方面,我们尚未看到许多旨在减轻传统平台威胁的隐私保护工具的平行性。本文旨在通过根据对所收集的68种出版物的研究,提出数据属性、保护和对手的全面分类,将关于VR隐私威胁和应对措施的知识系统化。我们对与VR所固有的各种数据源相关的风险进行统计分析,以考虑到已知的攻击和防御。我们希望通过重点突出突出突出突出突出的突出机会,从而推动和指导对这个日益重要的领域进行进一步的研究。