Resilient Countermeasures Against Cyber-Attacks on Self-Driving Car Architecture

Self-driving cars, believed to be on track to become a seven trillion-dollar industry by 2050, are likely to be a popular mode of transportation in the near future, as the technology promises safety and efficiency. Significant advances have been made to achieve these objectives. However, the idea of a self-driving car completing its goals without human intervention in the presence of uncertainties is still posed with challenges. These challenges mostly relate to decision-making under uncertainties that could arise from transient faults or deliberate attempts to disrupt the system in favor of adversarial motives. Traditional schemes of hardening the system against known compromises will not suffice primarily because of the sophistication adversarial attempts have come to achieve and the rate at which new attacks are being devised. The problem demands a solution that is resilient to attacks and that would allow a self-driving vehicle to complete its designated task in the presence of attacks or faults. Several attempts have been made towards achieving resilience in autonomous vehicles. To the best of our knowledge, this is the first work to give a thorough review on the resilient approaches adopted in the context and presents a taxonomy of such approaches. The paper also includes a brief introduction to the architecture of self-driving vehicles and its vulnerabilities in the presented context. This paper also discusses a novel approach using N-version programming for resilience.