By focusing on immersive interaction among users, the burgeoning Metaverse can be viewed as a natural extension of existing social media. Similar to traditional online social networks, there are numerous security and privacy issues in the Metaverse (e.g., attacks on user authentication and impersonation). In this paper, we develop a holistic research agenda for zero-trust user authentication in social virtual reality (VR), an early prototype of the Metaverse. Our proposed research includes four concrete steps: investigating biometrics-based authentication that is suitable for continuously authenticating VR users, leveraging federated learning (FL) for protecting user privacy in biometric data, improving the accuracy of continuous VR authentication with multimodal data, and boosting the usability of zero-trust security with adaptive VR authentication. Our preliminary study demonstrates that conventional FL algorithms are not well suited for biometrics-based authentication of VR users, leading to an accuracy of less than 10%. We discuss the root cause of this problem, the associated open challenges, and several future directions for realizing our research vision.
翻译:通过注重用户之间的即时互动,新兴的元数据可被视为现有社交媒体的自然延伸。与传统的在线社交网络类似,Metverse有许多安全和隐私问题(例如攻击用户认证和冒名顶替)。在本文中,我们为社会虚拟现实中的零信任用户认证(VR)制定了一个整体研究议程,这是Meteve的早期原型。我们提议的研究包括四个具体步骤:调查适合不断认证VR用户的生物鉴别认证,利用联合学习(FL)保护生物鉴别数据的用户隐私,提高连续VR认证与多式联运数据的准确性,提高零信任安全与适应性VR认证的可用性。我们的初步研究表明,常规的FL算法并不适合于基于生物鉴别的VR用户认证,导致不到10%的准确率。我们讨论了这一问题的根源、相关的公开挑战以及实现我们研究愿景的若干未来方向。