False Reality: Uncovering Sensor-induced Human-VR Interaction Vulnerability

Fuente: arXiv
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Autori principali: Jiang, Yancheng, Jiang, Yan, Zhou, Ruochen, Chen, Yi-Chao, Ji, Xiaoyu, Xu, Wenyuan
Natura: Preprint
Pubblicazione: 2025
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author Jiang, Yancheng
Jiang, Yan
Zhou, Ruochen
Chen, Yi-Chao
Ji, Xiaoyu
Xu, Wenyuan
author_facet Jiang, Yancheng
Jiang, Yan
Zhou, Ruochen
Chen, Yi-Chao
Ji, Xiaoyu
Xu, Wenyuan
contents Virtual Reality (VR) techniques, serving as the bridge between the real and virtual worlds, have boomed and are widely used in manufacturing, remote healthcare, gaming, etc. Specifically, VR systems offer users immersive experiences that include both perceptions and actions. Various studies have demonstrated that attackers can manipulate VR software to influence users' interactions, including perception and actions. However, such attacks typically require strong access and specialized expertise. In this paper, we are the first to present a systematic analysis of physical attacks against VR systems and introduce False Reality, a new attack threat to VR devices without requiring access to or modification of their software. False Reality disturbs VR system services by tampering with sensor measurements, and further spoofing users' perception even inducing harmful actions, e.g., inducing dizziness or causing users to crash into obstacles, by exploiting perceptual and psychological effects. We formalize these threats through an attack pathway framework and validate three representative pathways via physical experiments and user studies on five commercial VR devices. Finally, we further propose a defense prototype to mitigate such threats. Our findings shall provide valuable insights for enhancing the security and resilience of future VR systems.
format Preprint
id arxiv_https___arxiv_org_abs_2508_08043
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle False Reality: Uncovering Sensor-induced Human-VR Interaction Vulnerability
Jiang, Yancheng
Jiang, Yan
Zhou, Ruochen
Chen, Yi-Chao
Ji, Xiaoyu
Xu, Wenyuan
Cryptography and Security
Human-Computer Interaction
Virtual Reality (VR) techniques, serving as the bridge between the real and virtual worlds, have boomed and are widely used in manufacturing, remote healthcare, gaming, etc. Specifically, VR systems offer users immersive experiences that include both perceptions and actions. Various studies have demonstrated that attackers can manipulate VR software to influence users' interactions, including perception and actions. However, such attacks typically require strong access and specialized expertise. In this paper, we are the first to present a systematic analysis of physical attacks against VR systems and introduce False Reality, a new attack threat to VR devices without requiring access to or modification of their software. False Reality disturbs VR system services by tampering with sensor measurements, and further spoofing users' perception even inducing harmful actions, e.g., inducing dizziness or causing users to crash into obstacles, by exploiting perceptual and psychological effects. We formalize these threats through an attack pathway framework and validate three representative pathways via physical experiments and user studies on five commercial VR devices. Finally, we further propose a defense prototype to mitigate such threats. Our findings shall provide valuable insights for enhancing the security and resilience of future VR systems.
title False Reality: Uncovering Sensor-induced Human-VR Interaction Vulnerability
topic Cryptography and Security
Human-Computer Interaction
url https://arxiv.org/abs/2508.08043