MicGuard: A Comprehensive Detection System against Out-of-band Injection Attacks for Different Level Microphone-based Devices

The integration of microphones into sensors and systems, serving as input interfaces to intelligent applications and industrial manufacture, has raised growing public concerns regarding their input perception. Studies have uncovered the threat of out-of-band injection attacks on microphones, encompassing ultrasound, laser, and electromagnetic attacks, injecting commands or interferences for malicious intentions. However, existing efforts are limited to defense against ultrasound injections, overlooking the risks posed by other out-of-band injections. To address this gap, this paper proposes MicGuard, a comprehensive passive detection system against out-of-band attacks. Without relying on prior information from attacking and victim devices, the key insight of MicGuard is to utilize carrier traces and spectral chaos observed by remaining injection phenomena across different levels of devices. The carrier traces are used in a prejudgment to fast reject partial injected signals, and the following memory-based detection model to distinguish anomaly based on the quantified chaotic entropy extracted from publicly available audio datasets. MicGuard is evaluated on a wide range of microphone-based devices including sensors, recorders, smartphones, and tablets, achieving an average AUC of 98% with high robustness and universality.