Augmented/Mixed Reality (AR/MR) devices are unique from other mobile systems because of their capability to offer an immersive multi-user collaborative experience. While previous studies have explored privacy and security aspects of multiple user interactions in AR/MR, a less-explored area is the vulnerability of gait privacy. Gait is considered a private state because it is a highly individualistic and a distinctive biometric trait. Thus, preserving gait privacy in emerging AR/MR systems is crucial to safeguard individuals from potential identity tracking and unauthorized profiling. This paper first introduces GaitExtract, a framework designed to automatically detect gait information in humans, shedding light on the nuances of gait privacy in AR/MR. In this paper, we designed GaitExtract, a framework that can automatically detect the outside gait information of a human and investigate the vulnerability of gait privacy in AR. In a user study with 20 participants, our findings reveal that participants were uniquely identifiable with an accuracy of up to 78% using GaitExtract. Consequently, we propose GaitGuard, a system that safeguards gait information of people appearing in the camera view of the AR/MR device. Furthermore, we tested GaitGuard in an MR collaborative application, achieving 22 fps while streaming mitigated frames to the collaborative server. Our user-study survey indicated that users are more comfortable with releasing videos of them walking when GaitGuard is applied to the frames. These results underscore the efficacy and practicality of GaitGuard in mitigating gait privacy concerns in MR contexts.

翻译：增强现实/混合现实（AR/MR）设备因其提供沉浸式多用户协作体验的能力而区别于其他移动系统。尽管已有研究探讨了AR/MR中多用户交互的隐私与安全问题，但步态隐私的脆弱性仍是一个较少被探索的领域。步态被视为一种私人状态，因为它是一种高度个性化且独特的生物特征标识。因此，在新型AR/MR系统中保护步态隐私对于防止个人身份追踪和未经授权的画像分析至关重要。本文首先提出GaitExtract——一种可自动检测人类步态信息的框架，揭示了AR/MR中步态隐私的细微特性。我们设计该框架以自动检测人类外部步态信息，并探究AR中步态隐私的脆弱性。在涉及20名参与者的用户研究中，我们发现使用GaitExtract能够以高达78%的准确率唯一识别参与者。为此，我们提出GaitGuard系统，用于保护AR/MR设备摄像头视野内人物的步态信息。进一步，我们在MR协作应用中测试GaitGuard，结果证明其能够以22帧/秒的帧率向协作服务器传输经处理的帧。用户调查研究显示，当帧图像应用了GaitGuard时，用户更愿意公开其行走视频。这些结果充分证明了GaitGuard在缓解MR场景中步态隐私问题方面的有效性和实用性。