Sensors are crucial for autonomous operation in robotic vehicles (RV). Physical attacks on sensors such as sensor tampering or spoofing can feed erroneous values to RVs through physical channels, which results in mission failures. In this paper, we present DeLorean, a comprehensive diagnosis and recovery framework for securing autonomous RVs from physical attacks. We consider a strong form of physical attack called sensor deception attacks (SDAs), in which the adversary targets multiple sensors of different types simultaneously (even including all sensors). Under SDAs, DeLorean inspects the attack induced errors, identifies the targeted sensors, and prevents the erroneous sensor inputs from being used in RV's feedback control loop. DeLorean replays historic state information in the feedback control loop and recovers the RV from attacks. Our evaluation on four real and two simulated RVs shows that DeLorean can recover RVs from different attacks, and ensure mission success in 94% of the cases (on average), without any crashes. DeLorean incurs low performance, memory and battery overheads.
翻译:对于机器人飞行器的自主操作而言,传感器是关键。对传感器的物理攻击,例如传感器篡改或涂鸦等传感器的物理攻击,可以通过物理渠道向飞行器提供错误的值,从而导致飞行任务失败。在本文件中,我们介绍了DeLorean,一个确保自动遥控飞行器不受物理攻击的全面诊断和恢复框架。我们认为一种强烈的物理攻击形式,称为传感器欺骗攻击(SDAs),在这种攻击中,敌人同时针对不同类型(甚至包括所有传感器)的多个传感器。在SDAs下,DeLorean检查攻击引起的错误,确定目标传感器,防止错误的传感器输入用于RV的反馈控制循环。DeLorean在反馈控制循环中重播历史状态信息,并从攻击中恢复RV。我们对4个真实的和2个模拟RVs的评估显示,DeLorean可以从不同的攻击中恢复RVs,并确保94%的案件(平均)在不发生任何碰撞的情况下成功执行任务。DeLorean产生低性、记忆和电池顶部。