Yan Jiang (Zhejiang University), Xiaoyu Ji (Zhejiang University), Yancheng Jiang (Zhejiang University), Kai Wang (Zhejiang University), Chenren Xu (Peking University), Wenyuan Xu (Zhejiang University)

Sensors are key components to enable various applications, e.g., home intrusion detection, and environment monitoring. While various software defenses and physical protections are used to prevent sensor manipulation, this paper introduces a new threat vector, PowerRadio, which can bypass existing protections and change the sensor readings at a distance. PowerRadio leverages interconnected ground (GND) wires, a standard practice for electrical safety at home, to inject malicious signals. The injected signal is coupled by the sensor's analog measurement wire and eventually, it survives the noise filters, inducing incorrect measurement. We present three methods that can manipulate sensors by inducing static bias, periodical signals, or pulses. For instance, we show adding stripes into the captured images of a surveillance camera or injecting inaudible voice commands into conference microphones. We study the underlying principles of PowerRadio and find its root causes: (1) the lack of shielding between ground and data signal wires and (2) the asymmetry of circuit impedance that enables interference to bypass filtering. We validate PowerRadio against a surveillance system, broadcast system, and various sensors. We believe that PowerRadio represents an emerging threat that exhibits the pros of both radiated and conducted EMI, e.g., expanding the effective attack distance of radiated EMI yet eliminating the requirement of line-of-sight or approaching physically. Our insights shall provide guidance for enhancing the sensors' security and power wiring during the design phases.

View More Papers

Rethink Custom Transformers for Binary Analysis

Heng Yin, Professor, Department of Computer Science and Engineering, University of California, Riverside

Read More

Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication...

Jung-Woo Chang (University of California, San Diego), Ke Sun (University of California, San Diego), Nasimeh Heydaribeni (University of California, San Diego), Seira Hidano (KDDI Research, Inc.), Xinyu Zhang (University of California, San Diego), Farinaz Koushanfar (University of California, San Diego)

Read More

Black-box Membership Inference Attacks against Fine-tuned Diffusion Models

Yan Pang (University of Virginia), Tianhao Wang (University of Virginia)

Read More

Revisiting EM-based Estimation for Locally Differentially Private Protocols

Yutong Ye (Institute of software, Chinese Academy of Sciences & Zhongguancun Laboratory, Beijing, PR.China.), Tianhao Wang (University of Virginia), Min Zhang (Institute of Software, Chinese Academy of Sciences), Dengguo Feng (Institute of Software, Chinese Academy of Sciences)

Read More