Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.15865

Penetrating the Reality Wall: Long-Range and Through-Wall AR/VR Privacy Eavesdropping via Wireless Power Side Channel

Tao Ni·Zehua Sun·Yihe Zhou·Yuefeng Du·Qingchuan Zhao·Cong Wang
View original source ↗Read source document ↗Export metadata ↓

Abstract

Over the past decade, Metaverse technology (AR/VR) has seen widespread adoption in numerous areas, including gaming, social networking, and online collaboration. Although recent studies have exposed vulnerabilities in VR systems, they often apply methods (e.g., pre-installed malicious apps or scripts) from conventional mobile platforms directly, demonstrating impractical attacks that fail to investigate unique privacy leakages specific to VR platforms. In this paper, we present an orthogonal attempt to analyze the attack surface of the power side channel on AR/VR's network connection by capturing the through-wall wireless power in the network transmission medium (e.g., Wi-Fi signals) non-intrusively in a comparatively long distance (e.g., 5.0m-8.0m) and further reconstructing multi-level privacy-aware user behaviors. We propose MetaSpy to validate the feasibility and practicality of our disclosed wireless power-based traffic analysis attack. It first captures through-wall wireless power transmitted from the Wi-Fi router of an adjacent room, identifies the device type, then infers (i) user interactions such as browsing websites, running AR/VR apps, and performing various in-app activities, (ii) unseen VR-specific activities in VR games (e.g., Population: ONE), and (iii) avatar-based user re-identification and virtual keystroke inference corresponding to head movements. We evaluated the effectiveness of MetaSpy in four commercial-off-the-shelf (COTS) VR headsets, and the empirical results demonstrate its competitive accuracy in unveiling multi-level user privacy within virtual scenes in through-wall settings at a longer distance (1.8x-80x) than most of the recent studies, and it shows resilience to a series of external interference and impact factors. In addition, we also propose and evaluate effective countermeasures to protect data confidentiality in AR/VR wireless transmission.

Explore related subjects

cs.CR

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tao Ni, Zehua Sun, Yihe Zhou, Yuefeng Du, Qingchuan Zhao, Cong Wang. 2026-10-11. Penetrating the Reality Wall: Long-Range and Through-Wall AR/VR Privacy Eavesdropping via Wireless Power Side Channel. https://doi.org/10.1145/3830454.3832587

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Simulation-Secure Functional Encryption in the Bounded Storage Model

Functional encryption (FE) is a versatile paradigm that enables fine-grained access control over encrypted data. Despite its potential, achieving the gold standard of simulation-based security for FE is impossible in full generality. Known impossibility results demonstrate that simulation security cannot be attained if an adversary in the security experiment is permitted either an unbounded number of functional key queries or an unbounded number of challenge ciphertexts. In this work, we circumvent these fundamental barriers by considering two distinct memory-restricted settings: the Bounded Quantum Storage Model and the Bounded Classical Storage Model. In these settings, the plain model impossibility results no longer apply, allowing us to obtain new positive results. Specifically, we construct two adaptively simulation-secure FE schemes in the Bounded Quantum Storage Model: 1) Many functional key scheme: A construction supporting many functional key queries and a single challenge ciphertext, assuming only the existence of one-way functions. 2) Many ciphertext scheme: An information-theoretic secure construction supporting a single non-adaptive functional key, many challenge ciphertexts, and many adaptive functional key queries. Furthermore, we demonstrate that both schemes can be ported to the Bounded Classical Storage Model, assuming the existence of disappearing grey-box obfuscation.

cs.CR↗
arXiv2026

Watermarking Continuous Tabular Data Generation

In this paper, we introduce a simple yet effective tabular data watermarking mechanism with statistical guarantees. We show theoretically that the proposed watermark can be effectively detected, while faithfully preserving the data fidelity, and also demonstrates appealing robustness against additive noise attack. The general idea is to achieve the watermarking through a strategic embedding based on simple data binning. Specifically, it divides the feature's value range into finely segmented intervals and embeds watermarks into selected ``green list" intervals. To detect the watermarks, we develop a principled statistical hypothesis-testing framework with minimal assumptions: it remains valid as long as the underlying data distribution has a continuous density function. The watermarking efficacy is demonstrated through rigorous theoretical analysis and empirical validation, highlighting its utility in enhancing the security of synthetic and real-world datasets.

cs.CR↗
arXiv2026

MIRANDA: short signatures from a leakage-free full-domain-hash scheme

We present $\mathsf{Miranda}$, the first family of full-domain-hash signatures based on matrix codes. This signature scheme fulfils the paradigm of Gentry, Peikert and Vaikuntanathan ($\mathsf{GPV}$), which gives strong security guarantees. Our trapdoor is very simple and generic: if we propose it with matrix codes, it can actually be instantiated in many other ways since it only involves a subcode of a decodable code (or lattice) in a unique decoding regime of parameters. Though $\mathsf{Miranda}$ signing algorithm relies on a decoding task where there is exactly one solution, there are many possible signatures given a message to sign and we ensure that signatures are not leaking information on their underlying trapdoor by means of a very simple procedure involving the drawing of a small number of uniform bits. In particular $\mathsf{Miranda}$ does not use a rejection sampling procedure which makes its implementation a very simple task contrary to other $\mathsf{GPV}$-like signatures schemes such as $\mathsf{Falcon}$ or even $\mathsf{Wave}$. We instantiate $\mathsf{Miranda}$ with the famous family of Gabidulin codes represented as spaces of matrices and we study thoroughly its security (in the EUF-CMA security model). For~$128$ bits of classical security, the signature sizes are as low as~$90$ bytes and the public key sizes are in the order of~$2.6$ megabytes.

cs.CR↗