ADC-Bank: Detecting Acoustic Out-of-Band Signal Injection on Inertial Sensors

Inertial sensors are widely used in navigation, motion tracking, and gesture recognition systems. However, these sensors are vulnerable to spoofing attacks, where an attacker injects a carefully designed acoustic signal to trick the sensor readings. Traditional approaches to detecting and mitigating attacks rely on module redundancy, i.e., adding multiple sensor modules to increase robustness. However, this approach is not always feasible due to the limited space and increased complexity of current printed circuit boards. This paper proposes a new method, ADC-Bank, to detect inertial sensor spoofing attacks via acoustic out-of-band signals. Unlike other multiple-sensor-based solutions, it is based on component redundancy within one sensor, using multiple analog-to-digital converters (ADCs) with different sampling rates to simultaneously sample the output of the sensors. The different sample rates result in different aliasing frequencies for out-of-band signals that can be used to detect attacks. The proposed method is evaluated on off-the-shelf inertial sensors with commercial ADCs, demonstrating its ability to detect the attacking signals with relatively low cost and computation overhead.