RISiren: Wireless Sensing System Attacks via Metasurface

Abstract

After over a decade of intensive research, wireless sensing technology is nearing commercialization. However, the inherent openness of the wireless medium exposes this technology to security flaws and vulnerabilities. In this paper, we introduce RISiren to reveal the risk. RISiren is a pioneering end-to-end black-box attack system leveraging programmable metasurface with a high level of stealthiness. The key insight of RISiren lies in its ability to generate malicious multipath using metasurface, thereby disrupting wireless channel metrics influenced by genuine human activities and facilitating malicious attacks. To ensure the effectiveness of RISiren, we propose a novel metasurface configuration strategy aiming at creating human-like activities that stem from a comprehensive analysis of how human activities impact wireless signal propagation. We have implemented and validated RISiren using commercial WiFi devices. Our evaluation involved testing our attack strategies against five state-of-the-art systems (including five different types of recognition frameworks) representative of the current landscape. The experimental results show that the adversarial wireless signals generated by RISiren achieve over 90% attack success rate on average, and remain robust and effective across different environments and deployment setups, including through wall attack scenarios.