WordWhisper: Exploiting Real-Time, Hardware-Dependent IoT Communication Against Eavesdropping

Secure protocol-independent communication is increasingly demanding to support information exchange among neighbor Internet of Things (IoT) devices. For example, recent works utilize ultrasound at the resonant frequency range of a gyroscope to build communication between a speaker and the gyroscope. However, they are vulnerable to eavesdropping attacks and may have limitations in communication delays. In this work, we present WordWhisper, an efficient, word-level, and speaker-to-gyroscope communication system, with which only the target device can receive the correct information. We theoretically analyze Micro-Electro-Mechanical System (MEMS) gyroscope resonance and propose a hardware-dependent mechanism to defend against eavesdropping, making non-target gyroscopes receive ineffective information. Note that WordWhisper is free of costly data collection from gyroscopes, we train and update our decoding model based on the synthesized data (generated from theoretical MEMS resonance analysis) rather than the costly collected data from gyroscopes. Meanwhile, we address the challenge of eavesdropping when it comes to multiple attackers. We evaluate WordWhisper over 50 MEMS gyroscopes and 100 words. Extensive evaluations demonstrate that WordWhisper can achieve word-level communication with 99.33% accuracy while the recognition accuracy drops to a random guess for the non-target. Our decoding delay is lower than 0.63 seconds.