Tao Ni (City University of Hong Kong), Yuefeng Du (City University of Hong Kong), Qingchuan Zhao (City University of Hong Kong), Cong Wang (City University of Hong Kong)

Virtual Reality (VR) technologies are increasingly employed in numerous applications across various areas. Therefore, it is essential to ensure the security of interactions between users and VR devices. In this paper, we disclose a new side-channel leakage in the constellation tracking system of mainstream VR platforms, where the infrared (IR) signals emitted from the VR controllers for controller-headset interactions can be maliciously exploited to reconstruct unconstrained input keystrokes on the virtual keyboard non-intrusively. We propose a novel keystroke inference attack named VRecKey to demonstrate the feasibility and practicality of this novel infrared side channel. Specifically, VRecKey leverages a customized 2D IR sensor array to intercept ambient IR signals emitted from VR controllers and subsequently infers (i) character-level key presses on the virtual keyboard and (ii) word-level keystrokes along with their typing trajectories. We extensively evaluate the effectiveness of VRecKey with two commercial VR devices, and the results indicate that it can achieve over 94.2% and 90.5% top-3 accuracy in inferring character-level and word-level keystrokes with varying lengths, respectively. In addition, empirical results show that VRecKey is resilient to several practical impact factors and presents effectiveness in various real-world scenarios, which provides a complementary and orthogonal attack surface for the exploration of keystroke inference attacks in VR platforms.

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VulShield: Protecting Vulnerable Code Before Deploying Patches

Yuan Li (Zhongguancun Laboratory & Tsinghua University), Chao Zhang (Tsinghua University & JCSS & Zhongguancun Laboratory), Jinhao Zhu (UC Berkeley), Penghui Li (Zhongguancun Laboratory), Chenyang Li (Peking University), Songtao Yang (Zhongguancun Laboratory), Wende Tan (Tsinghua University)

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Eclipse Attacks on Monero's Peer-to-Peer Network

Ruisheng Shi (Beijing University of Posts and Telecommunications), Zhiyuan Peng (Beijing University of Posts and Telecommunications), Lina Lan (Beijing University of Posts and Telecommunications), Yulian Ge (Beijing University of Posts and Telecommunications), Peng Liu (Penn State University), Qin Wang (CSIRO Data61), Juan Wang (Wuhan University)

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CCTAG: Configurable and Combinable Tagged Architecture

Zhanpeng Liu (Peking University), Yi Rong (Tsinghua University), Chenyang Li (Peking University), Wende Tan (Tsinghua University), Yuan Li (Zhongguancun Laboratory), Xinhui Han (Peking University), Songtao Yang (Zhongguancun Laboratory), Chao Zhang (Tsinghua University)

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