2023/11/23 by Wei Sun, Sun, Wei, Yuwei Xiao +5 · 1 citation
Computer Science · Engineering · #FOS: Computer and information sciences #Green IT and Sustainability #H.5.2 #Human-Computer Interaction (cs.HC) #Power Line Communications and Noise #User Authentication and Security Systems
paper · pdf · doi:10.48550/arxiv.2311.13761
openalex publication_date 2023/11/23 · openalex created_date 2023/11/28 · openalex updated_date 2026/07/28
Internet of Things (IoT) devices are typically designed to function in a secure, closed environment, making it difficult for users to comprehend devices' behaviors. This paper shows that a user can leverage side-channel information to reason fine-grained internal states of black box IoT devices. The key enablers for our design are a multi-model sensing technique that fuses power consumption, network traffic, and radio emanations and an annotation interface that helps users form mental models of a black box IoT system. We built a prototype of our design and evaluated the prototype with open-source IoT devices and black-box commercial devices. Our experiments show a false positive rate of 1.44% for open-source IoT devices' state probing, and our participants take an average of 19.8 minutes to reason the internal states of black-box IoT devices.