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NDSS2023顶会

MetaWave: Attacking mmWave Sensing with Meta-material-enhanced Tags

Xingyu Chen, Zhengxiong Li, Baicheng Chen, Yi Zhu, Chris Xiaoxuan Lu, Zhengyu Peng, Feng Lin, Wenyao Xu, Kui Ren, Chunming Qiao

出版方
2023年份
9顶会引用

摘要

—Millimeter-wave (mmWave) sensing has been applied in many critical applications, serving millions of thousands of people around the world. However, it is vulnerable to attacks in the real world. These attacks are based on expensive and professional radio frequency (RF) modulator-based instruments and can be prevented by conventional practice (e.g., RF fingerprint). In this paper, we propose and design a novel passive mmWave attack, called MetaWave, with low-cost and easily obtainable meta-material tags for both vanish and ghost attack types. These meta-material tags are made of commercial off-the-shelf (COTS) materials with customized tag designs to attack various goals, which considerably low the attack bar on mmWave sensing. Specifically, we demonstrate that tags made of ordinal material (e.g., C-RAM LF) can be leveraged to precisely tamper the mmWave echo signal and spoof the range, angle, and speed sensing measurements. Besides, to optimize the attack, a general simulator-based MetaWave attack framework is proposed and designed to simulate the tag modulation effects on the mmWave signal with advanced tag and scene parameters. We evaluate, MetaWave, the meta-material tag attack in both simulation and real-world experiments (i

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