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VRSafe: A Secure Virtual Keyboard to Mitigate Keystroke Inference in Virtual Reality

arXiv Security Archived Apr 24, 2026 ✓ Full text saved

arXiv:2604.21001v1 Announce Type: new Abstract: Password-based authentication is one of the most commonly used methods for verifying user identities, and its widespread usage continues in virtual reality (VR) applications. As a result, various forms of attacks on password-based authentication in traditional environments such as keystroke inference and shoulder surfing, are still effective in VR applications. While keystroke inference attacks on virtual keyboards have been studied extensively, fe

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    Computer Science > Cryptography and Security [Submitted on 22 Apr 2026] VRSafe: A Secure Virtual Keyboard to Mitigate Keystroke Inference in Virtual Reality Yijun Yuan, Na Du, Adam J. Lee, Balaji Palanisamy Password-based authentication is one of the most commonly used methods for verifying user identities, and its widespread usage continues in virtual reality (VR) applications. As a result, various forms of attacks on password-based authentication in traditional environments such as keystroke inference and shoulder surfing, are still effective in VR applications. While keystroke inference attacks on virtual keyboards have been studied extensively, few efforts have developed an effective and cost-efficient defense strategy to mitigate keystroke inferences in VR. To address this gap, this paper presents a novel QWERTY keyboard called \textit{VRSafe} that is resilient to keystroke inference attacks. The proposed keyboard carefully introduces false positive keystrokes into the information collected by attackers during the typing process, making the inference of the original password difficult. \textit{VRSafe} also incorporates a novel malicious login detector that can effectively identify unauthorized login attempts using credentials inferred from keystroke inference attacks with high detection rate and minimal time and memory cost. The proposed design is evaluated through both simulation experiments and a real-world user study, and the results show that \textit{VRSafe} can significantly reduce the accuracy of keystroke inference attacks while incurring a modest overhead from a usability standpoint. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2604.21001 [cs.CR]   (or arXiv:2604.21001v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2604.21001 Focus to learn more Submission history From: Yijun Yuan [view email] [v1] Wed, 22 Apr 2026 18:49:16 UTC (1,673 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Apr 24, 2026
    Archived
    Apr 24, 2026
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