Acoustic Attack Mitigation Approach for MEMS Inertial Sensors Using Change Point Detection on MhIMU Framework

A Micro Electromechanical System (MEMS)-based inertial sensor, which includes accelerometers and gyroscopes, finds extensive use in motion sensing applications across various sectors. One of the challenges associated with these types of inertial sensors is their vulnerability to acoustic signals at sensor resonant frequency. Given the extensive use of inertial sensors, preventing these malicious attacks becomes a primary concern. In this paper, multiple heterogeneous inertial sensors are fused to mitigate the effect of acoustic attacks on inertial sensors. The statistical process control technique is used here in a specific fashion that helps identify attacks in any of the sensors used in the platform. A wide range of Monte-Carlo simulations are used to classify the inertial sensor attack, and experiments with real-time attack scenarios prove the efficacy of the proposed methodology. The results indicate the strong capability of the proposed architecture in countering resonance-based attacks while safeguarding the inertial sensor's integrity.