Sensors are crucial for perception and autonomous operation in robotic vehicles (RV). Unfortunately, RV sensors can be compromised by physical attacks such as sensor tampering or spoofing. In this paper, we present DeLorean, a unified framework for attack detection, attack diagnosis, and recovering RVs from sensor deception attacks (SDA). DeLorean can recover RVs even from strong SDAs in which the adversary targets multiple heterogeneous sensors simultaneously. We propose a novel attack diagnosis technique that inspects the attack-induced errors under SDAs, and identifies the targeted sensors using causal analysis. DeLorean then uses historic state information to selectively reconstruct physical states for compromised sensors, enabling targeted attack recovery under single or multi-sensor SDAs. We evaluate DeLorean on four real and two simulated RVs under SDAs targeting various sensors, and we find that it successfully recovers RVs from SDAs in 93% of the cases.

翻译：传感器对于机器人车辆（RV）的感知与自主运行至关重要。然而，RV传感器易受物理攻击（如传感器篡改或欺骗）的破坏。本文提出DeLorean——一个统一框架，用于攻击检测、攻击诊断以及从传感器欺骗攻击（SDA）中恢复RV。即使面对攻击者同时针对多个异构传感器的强SDA，DeLorean也能有效恢复RV。我们提出了一种新颖的攻击诊断技术，该技术通过检查SDA下攻击引发的错误，并利用因果分析识别被攻击的传感器。随后，DeLorean利用历史状态信息，选择性地为受损传感器重建物理状态，从而实现对单一或多传感器SDA下的针对性攻击恢复。我们在四款真实RV和两款模拟RV上，针对不同传感器遭受SDA的场景进行了评估，发现DeLorean在93%的案例中成功恢复了受SDA攻击的RV。