车-路-云协同自动驾驶安全技术研究进展

孙康康; 李建华; 陈秀真; 过敏意

doi:10.11959/j.issn.2096-109x.2025058

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车-路-云协同自动驾驶安全技术研究进展

综述 | 更新时间：2025-11-08

- 车-路-云协同自动驾驶安全技术研究进展
- Research progress on autonomous driving security technology for vehicle-road-cloud collaboration
- 网络与信息安全学报 2025年11卷第5期页码：1-30
- 作者机构：
  
  1.上海交通大学计算机学院，上海 200240
  2.上海市信息安全综合管理技术研究重点实验室，上海 200240
- 作者简介：
  
  [ "孙康康（1993- ），男，山东滨州人，博士，上海交通大学助理研究员，主要研究方向为车联网及物联网安全、隐私保护、博弈论、分布式机器学习安全。" ]
  [ "李建华（1965- ），男，江西九江人，博士，上海交通大学教授、博士生导师，主要研究方向为信息内容安全技术、态势感知、网络安全。" ]
  [ "陈秀真（1977- ），女，山东聊城人，博士，上海交通大学副教授、博士生导师，主要研究方向为社交网络数据分析、车联网信息安全、安全检测与评估。" ]
  [ "过敏意（1963- ），男，江苏无锡人，博士，上海交通大学教授、博士生导师，主要研究方向为并行与分布式处理、云计算。" ]
- 基金信息：
  
  国家自然科学基金(U2003206;62501397;62471301);上海市科委“科技创新行动计划”(22511101202)
- DOI：10.11959/j.issn.2096-109x.2025058
  中图分类号： TP393.0
- 收稿：2025-01-10，
  
  修回：2025-05-28，
  
  纸质出版：2025-10-25
- 稿件说明：
移动端阅览
孙康康, 李建华, 陈秀真, 等. 车-路-云协同自动驾驶安全技术研究进展[J]. 网络与信息安全学报, 2025, 11(5): 1-30.

SUN K K, LI J H, CHEN X Z, et al. Research progress on autonomous driving security technology for vehicle-road-cloud collaboration[J]. Chinese Journal of Network and Information Security, 2025, 11(5): 1-30.
孙康康, 李建华, 陈秀真, 等. 车-路-云协同自动驾驶安全技术研究进展[J]. 网络与信息安全学报, 2025, 11(5): 1-30. DOI： 10.11959/j.issn.2096-109x.2025058.

SUN K K, LI J H, CHEN X Z, et al. Research progress on autonomous driving security technology for vehicle-road-cloud collaboration[J]. Chinese Journal of Network and Information Security, 2025, 11(5): 1-30. DOI： 10.11959/j.issn.2096-109x.2025058.

摘要

随着边缘智能技术的进步和城市化进程的加快，智能交通系统（intelligent transportation system

ITS）得到快速发展。车-路-云协同实现车联网中车-车、车-路、车-云数据协同共享，构建了更加高效的协作智能交通系统（cooperative-intelligent transportation system

C-ITS）。然而，车-路-云协同存在大量的安全威胁，严重阻碍了协同自动驾驶的发展。首先总结了车-路-云协同的发展现状，详细介绍了自动驾驶发展历史及车-路-云协同自动驾驶环境。然后系统性地将车-路-云协同中遇到的攻击及安全防御技术归纳成两类：针对经典信息安全机制的威胁与防御技术，主要从基于信息可用性、基于信息完整性、基于信息保密性、基于信息真实性、基于信息不可否认性5部分进行详细介绍；针对基于机器学习技术的威胁与防御技术，主要从集中式与分布式两部分进行分析。最后展望了车-路-云协同安全技术的发展方向和研究重点，主要从联邦学习、区块链技术、安全多方计算、零知识证明、差分隐私技术展开介绍。

Abstract

With the advancement of edge intelligence technology and the acceleration of urbanization

intelligent transportation systems (ITS) have experienced rapid development. Vehicle-road-cloud (VRC) collaboration was enabled through the coordinated sharing of vehicle-to-vehicle (V2V)

vehicle-to-road (V2R)

and vehicle-to-cloud (V2C) data in the Internet of vehicles

thereby constructing a more efficient cooperative intelligent transportation system (C-ITS). However

numerous security threats in VRC collaboration were found to severely impede the development of cooperative autonomous driving. The development status of VRC collaboration was first summarized

and the history of autonomous driving and the VRC-based autonomous driving environment were elaborated. Subsequently

attacks and security defense technologies in VRC collaboration were systematically categorized into two types: classical information security mechanisms and defense technologies

which were detailed from five aspects—information availability

integrity

confidentiality

authenticity

and non-repudiation; and machine learning-based security threats and defense technologies

which were analyzed from both centralized and distributed perspectives. Finally

future development directions and research priorities of VRC collaborative security technologies were forecasted

primarily covering federated learning

blockchain technology

secure multi-party computation

zero-knowledge proof

and differential privacy technology.

关键词

Keywords

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