Replay-based Recovery for Autonomous Robotic Vehicles from Sensor Deception Attacks

Sensors are crucial for autonomous operation in robotic vehicles (RV). Unfortunately, RV sensors can be compromised by physical attacks such as tampering or spoofing, leading to a crash. In this paper, we present DeLorean, a modelfree recovery framework for recovering autonomous RVs from sensor deception attacks (SDA). DeLorean is designed to recover RVs even from a strong SDA in which the adversary targets multiple heterogeneous sensors simultaneously (even all the sensors). Under SDAs, DeLorean inspects the attack induced errors, identifies the targeted sensors, and prevents the erroneous sensor inputs from being used to derive actuator signals. DeLorean then replays historic state information in the RV's feedback control loop for a temporary mitigation and recovers the RV from SDA. Our evaluation on four real and two simulated RVs shows that DeLorean can recover RVs from SDAs, and ensure mission success in 90.7% of the cases on average.