Research On User Privacy Security In Intelligent Parking System

With the increasing use of smart cars,people are facing the problem of difficult parking.In order to improve the parking efficiency of users,many researchers have begun to study intelligent parking systems.At present,the intelligent parking system connects the intelligent parking lots and users via the Internet.The user can find parking lots through the mobile phone,which improves the users’ parking efficiency.Although the use of the intelligent parking system brings people a convenient and comfortable life,the normal operation of the system is based on the analysis of massive data.Once the system information is leaked,the users’ privacy is made public.In the current research,people still focus on the construction and improvement of intelligent parking system,and rarely pay attention to the users’ privacy.Therefore,strengthening the users’ privacy security is the core content of this thesis.And the main content of this article is as follows:(1)In order to solve the privacy problem faced by users,the privacy policy library model is proposed in this thesis.The privacy policy library model is based on different privacy scheme.Firstly,users’ information is classified into non-location information and location information.Secondly,the multi-sensitive attribute anonymous model and the multi-level label differential privacy tree model are used to protect users non-location information and users’ location information respectively.Through the security analysis of the privacy policy library,it is concluded that the privacy policy library can ensures the privacy of users.At the same time,we perform an experimental simulation on the anonymous model,and from the simulation results,it can be seen that the anonymous model does not reduce its efficiency when protecting users’ non-location information.(2)The users’ location information involves the users’ trajectory privacy,so the users’ location information is the focus in this thesis.The multi-level lable differential privacy tree model based on differential privacy is proposed to protect users’ location privacy.Based on multi-level lable differential privacy algorithm,the users’ location information is divided into sensitive location information and non-sensitive location information.Then noise is added to the users’ sensitive location information,which not only ensures the users’ location privacy and security,but also preserves the originality of the data as much as possible.According to experimental results,the multi-level lable differential privacy tree can not only protect the privacy of users,but the data error is extremely small and the original practicality of the data is retained.