Research On Security Mechanism Of Internet Of Vehicles

Since 2015,the new revolution has taken place in China's automobile industry.The key word “V2X” have brought into people's attention with the networking and intelligence.Networking can establish effective network communication connection which break the isolated island effect among sensors,V2 X users,roadside infrastructure and cloud to provide the foundation for subsequent intelligent applications.Intelligence is beneficial to the development of autonomous driving scenarios.With the help of information fusion from multisource sensors transferred through network connection,cars can be drove smartly instead of human drivers by utilizing the simultaneous traffic information,V2 X mainly relies on the service provided by mobile communication networks,the complex transmission environment and the property of open air transmission may cause serious security risks.The transmitted signal is vulnerable to the illegal users wiretapping,counterfeiting or tampering resulting the serious damage to the network,human's life and assets.In order to enhance the security of the V2 X,especially to solve the problem of user identification at the scenario where the network infrastructure is not available due to the coverage hole,the physical layer security authentication technology is introduced into the application of the V2 X.However,the traditional physical layer security authentication mechanism used the fixed decision threshold to identify the legitimacy of users has little environmental adaptability,which may result in a low detection probability for legitimate users in a low SNR environment and a high false alarm probability for illegal users in a high SNR environment.In order to solve the above problems,an adaptive user decision threshold configuration method is proposed in this thesis,which explores the optimal threshold adaptive to the current transmission environment in a two-step manner.The proposed algorithm has significantly enhanced the performance on the noise resistance and user identification.