对比电动车与燃油车在通信攻击下的稳定性，发现电动车更抗攻击。
Conceptualizing and Modeling Communication-Based Cyberattacks on Automated Vehicles
- 构建六类消息级攻击向量，模拟不同车辆混行场景。
- 电动车队列速度波动小、间距振荡少，攻击后恢复更快。
- 提出三层次风险分类，帮助制定防御策略。
自适应巡航控制（ACC）正快速普及于电动汽车（EV）和内燃机汽车（ICE），虽提升交通效率，但也扩大了通信攻击面。由于两类动力系统对控制指令的响应机制不同，其网络安全韧性尚未量化。本文提出六种新型消息级攻击向量，并在环形道路仿真中系统性地改变ACC市场渗透率（MPR）及被攻陷车辆的空间分布。通过三层次风险分类，将扰动指标转化为可操作的防御优先级。所有仿真场景下，电动车队列表现出更低的速度标准差、更小的间距振荡以及更快的攻击后恢复能力，揭示了控制器与动力系统耦合带来的内在稳定性优势。研究为混合自动驾驶交通中攻击检测与缓解提供了量化依据。
原文摘要 · Abstract (English)
Adaptive Cruise Control (ACC) is rapidly proliferating across electric vehicles (EVs) and internal combustion engine (ICE) vehicles, enhancing traffic flow while simultaneously expanding the attack surface for communication-based cyberattacks. Because the two powertrains translate control inputs into motion differently, their cyber-resilience remains unquantified. Therefore, we formalize six novel message-level attack vectors and implement them in a ring-road simulation that systematically varies the ACC market penetration rates (MPRs) and the spatial pattern of compromised vehicles. A three-tier risk taxonomy converts disturbance metrics into actionable defense priorities for practitioners. Across all simulation scenarios, EV platoons exhibit lower velocity standard deviation, reduced spacing oscillations, and faster post-attack recovery compared to ICE counterparts, revealing an inherent stability advantage. These findings clarify how controller-to-powertrain coupling influences vulnerability and offer quantitative guidance for the detection and mitigation of attacks in mixed automated traffic.
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