Analyzing the Impact of Adversarial Attacks on C-V2X-Enabled Road Safety: An Age of Information Perspective

TL;DR

This paper investigates how adversarial resource starvation attacks on NR-V2X can compromise road safety by increasing the Age of Information, demonstrating a significant safety risk for autonomous driving systems.

Contribution

It introduces a novel resource starvation attack on NR-V2X and models its impact using AoI, highlighting vulnerabilities affecting autonomous vehicle safety.

Findings

Attack reduces SLR of time-sensitive applications by up to 15%.

AoI effectively measures the impact of attacks on NR-V2X.

Benign vehicles' selfish behavior worsens safety conditions.

Abstract

The Cellular Vehicle-to-Everything (C-V2X), introduced and developed by the 3GPP, is a promising technology for the Autonomous Driving System (ADS). C-V2X aims to fulfill the Service-Level Requirements (SLRs) of ADS to ensure road safety following the development of the latest version, i.e., the NR-V2X. However, vulnerabilities threatening road safety in NR-V2X persist that have yet to be investigated. Existing research primarily evaluates road safety based on successful packet receptions. In this work, we propose a novel resource starvation attack that exploits vulnerabilities in the resource allocation of NR-V2X to diminish the required SLRs, making the road condition unsafe for autonomous driving. Furthermore, we establish the Age of Information (AoI) as the predominant metric for estimating the impact of adversarial attacks on NR-V2X by constructing a Discrete-time Markov chain (DTMC) based analytical model and validating it through extensive simulations. Finally, our analysis underscores how the proposed attack on NR-V2X can lead to unsafe driving conditions by reducing the SLR of time-sensitive applications in ADS up to 15% from the target. Additionally, we observe that even benign vehicles act selfishly when resources are scarce, leading to further safety compromises.