Study On The Problem Of Trajectory Data Privacy Protection In VANET

With the rapid development of GPS and Mobile Ad Hoc Networks, Vehicular Ad hoc Networks( VANETs) has attracted great attention from governments, academia and Industry, and it has become a hot topic. At present, VANETs and industry 4, wearable devices become the three major research hotspots in the field of Internet of things.VANETs can realize the intelligent driving, traffic management and vehicle entertainment etc. However, opportunities and challenges coexist, the rapid development of VANETs is also facing the risk of data security, privacy leaks. In the future each car has more than 80 sensors, and the amount of data transmitted to the server every day can reach 100 MB,these data cover the vehicles and the user’s personal information, behavior patterns and other sensitive information, the attacker can through the analysis of the eavesdropping on the communication process in the broadcast message, data, forecast track, vehicle tracking to get the vehicle sensitive data. Personal privacy and personal security will be threatened.The first problem facing the deployment of VANETs is the privacy of data security issues.So if we want to scale the deployment of VANETs, the first problem is the issue of data privacy and security issues, and for VANETs, the most important data is the trajectory of the vehicle data.In this paper, first of all, we analyze the potential trajectory privacy issues of VANETs, and the network trajectory privacy problem under different application scenarios are analyzed, aiming at how to protect the car networking trajectory data privacy and prevent disclosure of sensitive information are described. This paper respectively introduces the current mainstream technology to privacy protection and explain the existence of the problem through analysis of existing privacy protection scheme comparison.According to the trajectory privacy issues in vehicular network, respectively in two application scenarios, which are network data transfer and data release process, this paper introduces the differential privacy thoughts of VANETs trajectory data privacy issues in the process of release. Through theoretical analysis, modeling and experiment, we exploresuitable for VANETs trajectory privacy protection mechanism. Through the theoretical analysis, modeling and experiments, explore the suitable vehicle networking track privacy protection mechanism. Finally, from two angles of data quality and track data availability,this paper proposes the privacy protection algorithm to evaluate the performance and compare with the existing privacy protection scheme. Experimental results show differential partition privacy in VANETs trajectory privacy protection not only achieve good privacy protection but also effective ease of communication pressure. For location based services compared with the existing GNoise mechanism and PNoise mechanism, the results show that good results are obtained in both data quality and privacy protection.