[论文解读] A Survey on Security Attacks and Defense Techniques for Connected and Autonomous Vehicles

Minh Trien Pham, Kaiqi Xiong|arXiv (Cornell University)|Jul 16, 2020

Vehicular Ad Hoc Networks (VANETs)参考文献 99被引用 24

一句话总结

本综述分析了2000至2020年间184篇关于联网与自动驾驶汽车（CAVs）安全威胁与防御的学术论文，按目标组件、访问需求和动机对攻击模型进行分类。研究发现学术研究与工业实现之间存在关键差距，尽管已有安全框架在开发中，但商业部署的CAVs仍缺乏对近期发现攻击向量的防御能力。

ABSTRACT

Autonomous Vehicle has been transforming intelligent transportation systems. As telecommunication technology improves, autonomous vehicles are getting connected to each other and to infrastructures, forming Connected and Autonomous Vehicles (CAVs). CAVs will help humans achieve safe, efficient, and autonomous transportation systems. However, CAVs will face significant security challenges because many of their components are vulnerable to attacks, and a successful attack on a CAV may have significant impacts on other CAVs and infrastructures due to their communications. In this paper, we conduct a survey on 184 papers from 2000 to 2020 to understand state-of-the-art CAV attacks and defense techniques. This survey first presents a comprehensive overview of security attacks and their corresponding countermeasures on CAVs. We then discuss the details of attack models based on the targeted CAV components of attacks, access requirements, and attack motives. Finally, we identify some current research challenges and trends from the perspectives of both academic research and industrial development. Based on our studies of academic literature and industrial publications, we have not found any strong connection between academic research and industry's implementation on CAV-related security issues. While efforts from CAV manufacturers to secure CAVs have been reported, there is no evidence to show that CAVs on the market have the ability to defend against some novel attack models that the research community has recently found. This survey may give researchers and engineers a better understanding of the current status and trend of CAV security for CAV future improvement.

研究动机与目标

• 对针对联网与自动驾驶汽车（CAVs）的安全攻击和防御机制进行全面分析。
• 根据目标组件、所需访问权限和攻击动机对攻击模型进行分类。
• 评估学术研究与CAV安全解决方案在工业实现中的对齐程度。
• 识别CAV网络安全领域中的开放研究挑战与未来研究方向。

提出的方法

• 对2000至2020年间184篇关于CAV安全的同行评审论文进行系统性文献综述。
• 根据目标组件（如传感器、通信系统、CAN总线）、访问需求（远程、本地、物理）和攻击动机（破坏、控制、数据窃取）对攻击模型进行分类。
• 分析包括安全开发生命周期（SDL）、威胁建模、渗透测试和安全通信协议在内的防御技术。
• 评估工业安全举措，如《自动驾驶安全第一》白皮书和Guardknox的CAN总线通信封锁技术。
• 对比学术发现与实际CAV安全实现，以识别研究与实践之间的差距。
• 识别CAV网络安全领域中的新兴趋势与未解决挑战。

实验结果

研究问题

• RQ1 CAVs中最易受网络攻击的组件是什么，它们如何成为攻击目标？
• RQ2 攻击模型在所需访问级别和攻击动机方面有何差异？
• RQ3 当前工业安全实践与学术研究在CAV威胁方面的对齐程度如何？
• RQ4 理论防御机制在研究中提出与在商业CAV系统中部署之间存在哪些关键差距？
• RQ5 未来哪些研究方向对提升CAV的安全性和可信度最为关键？

主要发现

• 学术研究与工业实现之间存在显著差距，市场成熟型CAVs并未表现出对近期研究中识别出的新攻击模型的防御能力。
• 许多CAV组件——如GPS、LiDAR、CAN总线和V2X通信系统——易受欺骗、干扰和注入攻击。
• 工业举措如《自动驾驶安全第一》白皮书倡导采用安全开发生命周期（SDL）和模型验证，但缺乏详细的技术实现指导。
• 专有解决方案如Guardknox的通信封锁技术提供了形式化验证的CAN总线安全防护，且硬件改动极少，但其在公开部署中仍有限。
• 尽管产业界已采取努力，但尚未有主要CAV制造商公开演示对感知系统高级对抗性攻击（如对抗性图像攻击）的防御能力。
• 已部署CAVs中缺乏标准化、可公开验证的安全更新与威胁响应机制，引发了对其长期系统韧性的担忧。