Cyber-physical Security Analysis of Teleoperated Autonomous Road Vehicles

Abstract

Automated road vehicles, commonly known as autonomous vehicles (AV) is a revolutionary step for next generation mobility services on public roads. The primary mission of AV is to improve safety and convenience in road transportation by deploying automated technology for the vehicle-driving tasks. Such automated technology comprises of various sensors, software, and hardware to receive vehicleâs mission, perceive the surrounding road environment, localize the vehicleâs position, plan the route, make decision on driving maneuvers and finally performing the driving actions. Teleoperated driving (ToD) for road vehicles, also known as remotely operated road vehicles (RORV) has originated to handle the corner case of AV with a driver-in-loop from a remote operating station. For such a system, the teleoperator can remotely control the steering, acceleration, and braking action of the vehicle. To perform these tasks, teleoperated vehicles require interaction with the operating environment using perception sensors, localization sensors and cellular communication. Though AV and ToD are considered promising technologies to reshape the mobility landscape for public roads, they also transform the road vehicles from physical systems to cyber-physical systems and introduce new categories of challenges. Cyber-physical threats of AV and ToD is one of the critical areas as it can compromise safety and operational capability of future mobility.Therefore, research on methods for security analysis specific to AV and ToD is necessary. This dissertation conducts the research focusing on this area by analyzing threat models, attack model and detection model by following systems theory approach, knowledge of the context and physical system and machine learning (ML) algorithm.⢠First, threat modeling of AV perception system is created using two approaches. First approach follows the standard 21434, jointly developed by International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE). The second approach follows the method of systems theoretic process analysis for security known as STPA-Sec. Next, a comparative study is done between the output of aforementioned ISO/SAE 21434 and STPA-Sec based threat models. In the final step, an integrated approach is proposed for object-focused impact rating and feasibility analysis of artificial intelligence (AI) based perception system for AV.⢠Second, a threat model for ToD is created with the attack-tree based approach. Based on high-risk attacks, an attack model with false data injection on steering control command is created.⢠Third, to detect such attack Physics-based Context-aware Anomaly Detection System (PCADS) is proposed and presented with results.The outcome of this research highlights the importance of developing a cyber-physical security framework for teleoperated AVs. Moreover, with thorough analysis of the experimental results, this dissertation recommends potential future steps to assist in fostering research direction for cyber-physical security of such systems.