MetaRFence: Protecting Human Motion Privacy Against RFID Sensing via Metasurface

Radio Frequency Identification (RFID) technology has emerged as a pervasive modality for human motion sensing in applications such as smart environments and healthcare monitoring. However, the inherent through-wall sensing capability of RFID technology raises critical privacy concerns regarding the unintended leakage of human motion information, a challenge that has not been adequately addressed. To fill this gap, we present a metasurface-based RFID sensing defence (MetaRFence), the first system designed to protect human motion privacy against adversarial through-wall RFID sensing. To this end, we first devise a programmable metasurface comprising 1-bit phase shifters to systematically obfuscate motion-induced signal patterns. Then, we characterize the metasurface's impact on RFID signals across temporal and spectral domains through comprehensive theoretical modeling and empirical investigations. However, our analysis reveals that it is non-trivial to achieve effective signal obfuscation in both domains, primarily due to a fundamental trade-off between increasing temporal signal variation and masking human motion in its spectrum. To overcome this, we judiciously devise a metasurface controlling strategy that jointly optimizes the signal entropy, variance, and spectrum distribution to reach a balance between temporal and spectral motion obfuscation. Our comprehensive experiments demonstrate thatMetaRFencereduces adversarial through-wall motion detection rates to$\leq$6%, decreases the F1-score of human gesture recognition to$\leq$0.11 on average, and amplifies respiration rate estimation errors by 3×, establishing a robust defense mechanism for RFID-based motion privacy protection.