论文标题
在Metaverse中隐藏着：在VR中实现理论上最佳的隐私性使用权衡
Going Incognito in the Metaverse: Achieving Theoretically Optimal Privacy-Usability Tradeoffs in VR
论文作者
论文摘要
虚拟现实（VR）触发应用程序和所谓的“元评估”承诺将成为下一个人类计算机互动的下一个主要媒介。但是，最近的研究表明，可以对VR用户进行介绍和脱名字的简便性，Metaverse平台具有许多传统互联网（以及更多）的隐私风险，而目前提供了几乎没有用户习惯的防御性公用事业。为了解决这个问题，我们提出了为VR实施“隐身模式”的第一种已知方法。我们的技术利用当地的差异隐私来量化掩盖敏感用户数据属性，重点是智能地添加何时何地添加何时何地，以最大程度地提高隐私，同时最大程度地减少可用性影响。我们的系统能够灵活地适应每个VR应用程序的独特需求，以进一步优化此权衡。我们将解决方案实现为通用统一（C＃）插件，然后使用几个流行的VR应用程序进行评估。忠实地复制最著名的VR隐私攻击研究后，我们在使用解决方案时表明了攻击者能力的显着退化。
Virtual reality (VR) telepresence applications and the so-called "metaverse" promise to be the next major medium of human-computer interaction. However, with recent studies demonstrating the ease at which VR users can be profiled and deanonymized, metaverse platforms carry many of the privacy risks of the conventional internet (and more) while at present offering few of the defensive utilities that users are accustomed to having access to. To remedy this, we present the first known method of implementing an "incognito mode" for VR. Our technique leverages local differential privacy to quantifiably obscure sensitive user data attributes, with a focus on intelligently adding noise when and where it is needed most to maximize privacy while minimizing usability impact. Our system is capable of flexibly adapting to the unique needs of each VR application to further optimize this trade-off. We implement our solution as a universal Unity (C#) plugin that we then evaluate using several popular VR applications. Upon faithfully replicating the most well-known VR privacy attack studies, we show a significant degradation of attacker capabilities when using our solution.
