Forgery Node Detection Algorithm Based On Location Services In The Internet Of Vehicles

With the rapid development of mobile Internet,the location service technology in the Internet of Vehicles has been widely used.However,in the Internet of Vehicles,vehicles that report traffic information to each other in a self-organized manner are dominant.In complex network environment,the normal behavior of other vehicle nodes may be interfered by some internal vehicle nodes by sending abnormal traffic information.Therefore,it can be seen from the impact of the behavior of launching such an attack node on the safety of the Internet of Vehicles that the vehicle node threatens the safety of the Internet of Vehicles by destroying the route or destroying the data,which may cause the driver's personal safety and property in more serious cases.Therefore,based on the existing research,in the thesis,the features of the forgery nodes of the Internet of Vehicles are studied.Based on traffic information,detection model of the forgery nodes of the Internet of Vehicles is constructed.Based on the dynamic reputation value,detection algorithm of the forgery nodes of the Internet of Vehicles is designed.The specific research work is as follows:1.In order to improve the behavior features of the forgery nodes of the Internet of Vehicles,a double layer detection feature parameter of multiple nodes in Internet of Vehicles is designed.First,the common types of nodes in the Internet of Vehicles are summarized,which are divided into normal nodes,non-cooperative nodes and malicious attack nodes.Then,a four-tuple description method is designed to describe qualitatively the common types of nodes in the Internet of Vehicles.Finally,the behavior features and relevance of various types of Internet of Vehicle nodes are analyzed.Double layer detection feature parameters,while constructing correlation detection to verify its effectiveness in accuracy and calculation time.2.In order to improve the compliance of the forgery node detection model of the Internet of Vehicles,a forgery node detection model based on traffic information is constructed in Internet of Vehicles.First,the road traffic information and its types published,forwarded and received by the nodes in the Internet of Vehicles are defined,and then the effective features common in the traffic information are extracted to form an effective feature vector.On this basis,a forgery node detection model based on traffic information is constructed.3.In order to optimize the Internet of Vehicles forgery node detection algorithm,a forgery node detection algorithm based on dynamic reputation value is proposed.First,the support vector machine is used to detect the traffic information published,forwarded and sent by the vehicle node,then the trust vector table is used to record the historical state,and then the dynamic reputation value of the node is calculated.Finally,simulation experiments show that the time cost of detecting the forgery nodes of the Internet of Vehicles is reduced and the accurate detection rate of the forgery nodes of the Internet of Vehicles is improved.The research results of the thesis can effectively detect the forgery nodes of the Internet of Vehicles,which is of great significance to promoting the research of Internet of Vehicles security technology,promoting the application of Internet of Vehicles and improving the quality of life of people.