Guardauto: A Decentralized Runtime Protection System for Autonomous Driving
This addresses safety and security issues for autonomous driving systems, but it is incremental as it builds on existing protection methods.
The paper tackles the problem of runtime safety and security threats in autonomous vehicles by proposing Guardauto, a decentralized self-protection framework that isolates components and monitors execution, resulting in effective mitigation of failures and attacks with acceptable performance overhead.
Due to the broad attack surface and the lack of runtime protection, potential safety and security threats hinder the real-life adoption of autonomous vehicles. Although efforts have been made to mitigate some specific attacks, there are few works on the protection of the self-driving system. This paper presents a decentralized self-protection framework called Guardauto to protect the self-driving system against runtime threats. First, Guardauto proposes an isolation model to decouple the self-driving system and isolate its components with a set of partitions. Second, Guardauto provides self-protection mechanisms for each target component, which combines different methods to monitor the target execution and plan adaption actions accordingly. Third, Guardauto provides cooperation among local self-protection mechanisms to identify the root-cause component in the case of cascading failures affecting multiple components. A prototype has been implemented and evaluated on the open-source autonomous driving system Autoware. Results show that Guardauto could effectively mitigate runtime failures and attacks, and protect the control system with acceptable performance overhead.