VIMU: Effective Physics-based Realtime Detection and Recovery against Stealthy Attacks on UAVs

Abstract

Sensor attacks on robotic vehicles have become pervasive and manipulative. Their latest advancements exploit sensor and detector characteristics to bypass detection. Recent security efforts have leveraged the physics-based model to detect or mitigate sensor attacks. However, these approaches are only resilient to a few sensor attacks and still need improvement in detection effectiveness. We present VIMU, an efficient sensor attack detection and resilience system for unmanned aerial vehicles. We propose a detection algorithm, CS-EMA, that leverages low-pass filtering to identify stealthy gyroscope attacks while achieving an overall effective sensor attack detection. We develop a fine-grained nonlinear physical model with precise aerodynamic and propulsion wrench modeling. We also augment the state estimation with a FIFO buffer safeguard to mitigate the impact of high-rate IMU attacks. The proposed physical model and buffer safeguard provide an effective system state recovery toward maintaining flight stability. We implement VIMU on PX4 autopilot. The evaluation results demonstrate the effectiveness of VIMU in detecting and mitigating various realistic sensor attacks, especially stealthy attacks.