SCVMON: Data-oriented attack recovery for RVs based on safety-critical variable monitoring

Abstract

There are many various data-oriented attacks on robotic vehicles (RVs) that change the inputs of an RV control program. While much research has been dedicated to detecting the attacks, the recovery mechanism has received relatively less attention. Without recovery after detection, an RV cannot continue with its assigned missions. Unfortunately, the existing recovery mechanisms have limitations that make it difficult to deploy these in real RVs, such that they require additional hardware/software or can only recover from the limited types of data-oriented attacks. To overcome these limitations, we propose a framework called SCVMON that detects and helps RVs recover from various data-oriented attacks that generate inappropriate control commands. Based on the observation that data-oriented attacks inevitably change the values of some variables in RV control programs, SCVMON systematically identifies the safety-critical variables (SCVs) that can affect the safety of RVs. For efficient recovery, we extract from SCVs a set of monitored safety-critical variables (mSCVs) that can reflect all input changes, and monitor them to detect and recover from various data-oriented attacks. SCVMON does not depend on the physical nature of a specific sensor or hardware, which is a significant benefit, and it can be applied through a simple software update. Our evaluation shows that SCVMON can quickly detect and recover from 20 types of data-oriented attacks. Also, SCVMON incurs only 0.3% storage overhead and up to 5.1% runtime overhead, proving that it is suitable for RVs.