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.

翻译：由3GPP提出并发展的蜂窝车联网（C-V2X）是自动驾驶系统（ADS）中一项前景广阔的技术。随着最新版本NR-V2X的发展，C-V2X致力于满足ADS的服务级别要求（SLRs）以确保道路安全。然而，NR-V2X中仍存在威胁道路安全的漏洞尚未得到深入研究。现有工作主要基于数据包成功接收率评估道路安全性。本文提出一种新颖的资源饥饿攻击，该攻击利用NR-V2X资源分配机制的漏洞削弱目标SLRs，导致道路环境不适用于自动驾驶。此外，我们通过构建基于离散时间马尔可夫链（DTMC）的理论模型并进行大量仿真验证，确立了信息年龄（AoI）作为评估对抗性攻击对NR-V2X影响的核心指标。最终分析表明，所提出的NR-V2X攻击可使ADS中时间敏感应用的SLR较目标值降低达15%，从而导致不安全驾驶状态。我们还观察到，在资源稀缺时即使良性车辆也会表现出自私行为，进而引发进一步的安全隐患。