利用Veins仿真评估对抗性交通模式对VANET通信的影响

中文摘要 AI 辅助

车载自组织网络（VANETs）是智能交通系统的关键组成部分，可实现车辆间的实时通信。然而其开放且动态的特性使其极易受到破坏通信可靠性的对抗性行为影响。本文采用集成了OMNeT++和SUMO的Veins仿真框架，研究对抗性交通模式对VANET性能的影响。我们在不同交通密度和移动性条件下，设计并评估了多种对抗场景，包括消息泛洪、虚假信息传播及协同拥塞攻击。研究测量了分组投递率（PDR）、端到端延迟和网络吞吐量等关键性能指标。实验结果表明，对抗性交通可使PDR降低多达96.55%，低密度下消息泛洪会导致吞吐量降低27.89%，并显著降低整体网络效率。该研究结果凸显了VANET通信中的关键漏洞，为设计更具弹性和安全性的车载网络提供了见解。

英文摘要

Vehicular Ad Hoc Networks (VANETs) are a key component of intelligent transportation systems, enabling real-time communication between vehicles. However, their open and dynamic nature makes them highly vulnerable to adversarial behaviors that can disrupt communication reliability. This paper investigates the impact of adversarial traffic patterns on VANET performance using the Veins simulation framework integrated with OMNeT++ and SUMO. We design and evaluate multiple adversarial scenarios, including message flooding, false information dissemination, and coordinated congestion attacks, under varying traffic densities and mobility conditions. The study measures key performance metrics such as packet delivery ratio (PDR), end-to-end delay, and network throughput. Experimental results show that adversarial traffic can reduce PDR by up to 96.55%, with message flooding at low density producing a throughput reduction of 27.89%, and significantly degrade overall network efficiency. The findings highlight critical vulnerabilities in VANET communication and provide insights into designing more resilient and secure vehicular networks.

发表机构

• Texas A&M University San Antonio（德克萨斯农工大学圣安东尼奥分校）

机构由 AI 辅助整理，请以论文原文为准。