智能网联车的信息安全是网络空间安全的重要组成部分，对确保智能车辆的安全、高效运行有重要的作用和意义。本课题针对网络拓扑快速动态变化、车辆相遇机会少、交互时间短等特征，围绕车联网安全及消息传播问题展开研究。借助于机器学习等方法，建立满足车联网应用要求的分布式车辆信任模型和机制，以快速定性和定量地刻画车辆间的信任关系和模型，使车辆具有主动学习和独立判周边车辆可信度的能力；借助于知识推理和学习机制，研究并建立消息的快速认证和检测机制，过滤虚假消息，使网络及道路资源不被恶意占用，避免车辆/驾驶员被干扰或误导；针对新一代的通信网络，研究并建立融合消息安全、隐私保护及消息安全传播于一体的新型高效消息传播机制，以实现消息的安全传播与认证；通过仿真实验和真实环境的测试，研究并建立车辆信息安全评估体系；为智能网联车走向应用奠定理论和技术基础。

The information security of intelligent connected vehicle is an important part of network space security, which plays an important role in ensuring the safe and efficient operation of intelligent vehicles. This topic focuses on the characteristics of rapid dynamic change, less opportunity of vehicle encounters and short time, and researches on the security of the Internet of vehicles and the issue of message communication. Meeting vehicle was established by using machine learning methods, such as networking application of distributed trust models and mechanisms, in a quick qualitative and quantitative model of trust relationship between the vehicle and the vehicle with active learning and independent ability to surrounding vehicles credibility; By means of knowledge reasoning and learning mechanism, the rapid certification and inspection mechanism, and establish the news filter virtual news, make the network resource is occupied by a malicious, avoid vehicle/driver be interference or misleading; Study of a new generation of communication network, and establish the fusion of message security, privacy and security transmission in the integration of new type of high efficient information dissemination mechanism, so as to realize the security of information transmission and certification; Through the simulation experiment and real environment test, the vehicle information security evaluation system is researched and established. It lays a theoretical and technical foundation for the application of intelligent connected vehicle.