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

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.e., 20 different environments) with various attack settings. Experimental results demonstrate that MetaWave can achieve up to 97% Top-1 attack accuracy on range estimation, 96% on angle estimation, and 91% on speed estimation in actual practice, 10-100X cheaper than existing mmWave attack methods. We also evaluate the usability and robustness of MetaWave under different real-world scenarios. Moreover, we conduct in-depth analysis and discussion on countermeasures for MetaWave mmWave attacks to improve wireless sensing and cyber-infrastructure security.