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

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.

💡 Research Summary

The paper investigates a novel class of MAC‑layer attacks on 5G NR‑V2X (New Radio Vehicle‑to‑Everything) that target the semi‑persistent scheduling (SPS) resource allocation mechanism used in Mode 2 (autonomous resource selection). While NR‑V2X was introduced to satisfy the stringent Service‑Level Requirements (SLRs) of autonomous driving systems (ADS), the authors demonstrate that an adversary equipped with standard‑compliant V2X hardware can subtly degrade safety without triggering conventional performance alarms such as packet reception ratio (PRR) or channel busy ratio (CBR).

Attack concept – The attacker (named Eve) exploits two recent protocol flexibilities: (i) the reduction of the sensing window from 1000 ms to 100 ms, and (ii) the ability to set the transmission periodicity (RRI) as low as 1 ms. By transmitting a burst of Basic Safety Messages (BSMs) at a very high rate and each time on a different candidate subframe resource (CSR), Eve makes those resources appear “reserved” to neighboring legitimate vehicles during their sensing phase. Consequently, a fraction x of the total sidelink resources becomes unavailable for legitimate reselection attempts. Importantly, Eve does not jam or corrupt already scheduled transmissions; she merely starves the system of free resources, thereby increasing the time between successful transmissions.

Analytical framework – To quantify the impact, the authors construct a discrete‑time Markov chain (DTMC) that captures the SPS state machine: (k, τ) states representing the remaining reselection counter (RC) and the countdown to the next transmission, plus an “Idle” state where a vehicle searches for a free CSR. Transition probabilities incorporate (a) the probability Psch of finding a suitable CSR in a normal environment, (b) the reduction factor (1 − x) due to the attack (P′sch = (1 − x)·Psch), and (c) the keep‑resource probability Pkeep that determines whether a vehicle retains its current CSR after RC expires.

The key performance metric is the Age of Information (AoI), defined as the elapsed time since the most recently received update was generated. By modeling the number of transmission attempts until a successful reception as a geometric random variable with PHY success probability φ, the authors derive closed‑form expressions for the expected inter‑success interval T and the AoI reset value D. The average AoI is then obtained via renewal theory:

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