| The widespread use of smart devices such as smart phones and tablets has greatly developed the mobile application market.more and more people need location-based services,such as navigation and weather information.These services can be obtained from any mobile device embedded with GPS chips.In location-based mobile applications,the user’s location information is sent to the server,and the server can collect,analyze and sell the information when it returns to the service,which opens the door for privacy disclosure,and then exposes the user’s sensitive information,such as family,workplace and even religious and political preferences.In recent years,in order to protect users’ privacy when using location-based services,many location privacy protection mechanisms have been proposed.These mechanisms are difficult to be protected in low-density areas,independent of the third party and server security.Therefore,this paper proposes three location privacy protection algorithms in different scenarios.The main work of this paper is as follows:(1)This paper proposes a disturbance cooperative location privacy protection algorithm based on P2 P architecture.In this algorithm,when a user(head node)needs location service,it first broadcasts a help request to the user node within the communication radius,then the user who wants to help the head node broadcast his position to the head node,and then the head node randomly selects two secondary nodes according to the nodes received in the limited time(if there are more than or equal to two secondary nodes to choose from),If not,the head node restarts the broadcast),respectively transmits two encrypted packets,and then the two secondary nodes broadcast the request message,and then select any one of the received nodes within the limited time to transmit the packets received from the head node.The two new users who own the packets repeat the process of the secondary node until the packets are transmitted to the service provider.Through this way of cooperation between users,the algorithm not only achieves the protection of user’s location privacy in P2 P environment,but also avoids the risk of service providers.The final experiment proves that.This scheme not only can effectively protect the privacy of users,but also has low communication cost and accurate service.(2)This paper proposes a static clustering k-anonymity algorithm based on k-anonymity algorithm and virtual location algorithm in P2 P environment.This algorithm mainly solves the problem that it is difficult for the disturbed cooperative algorithm to have enough users to transfer packets quickly under low-density users.As an enhancement of the disturbance cooperative algorithm,the static clustering k-anonymity algorithm can achieve good results in low-density user area.The main idea of static clustering k-anonymity algorithm is that users scan the surrounding area for request broadcast.If there is,they broadcast their own location and request.When they do not receive their own service report within the limited time,they act as the head node(or they act as the head node if they did not find the request message before scanning),and broadcast the request report to the surrounding area,Then,in a limited time,the optional users are randomly selected from the collected messages,and the fake locations and requests are generated according to the specially designed method.Finally,these locations and requests are sent to the service provider in a report.Algorithm analysis and experimental results show that the static clustering k-anonymity algorithm can not only effectively protect the user’s location privacy in low-density areas,but also provide high-quality services,in addition to avoiding the potential threat of service providers.(3)This paper proposes a low-speed clustering k-anonymity algorithm for low-speed mobile scene in P2 P environment.Based on the static clustering k-anonymity,the main idea is consistent with the static clustering k-anonymity algorithm.By reducing the limited time and changing the way that the head node uses the idea of virtual location to generate the pseudo node location and request,the algorithm improves the performance of the static clustering kanonymity algorithm,Taking the position of the head node at the moment before and at this moment as the trajectory guidance(detailed in Chapter 5 of the algorithm principle),we can create fake nodes to simulate the real user trajectory in low-speed scenes,so as to achieve the purpose of cheating eavesdroppers.Algorithm analysis and simulation results show that lowspeed clustering k-anonymity algorithm can provide good privacy protection ability when users continuously request location-based services in low-speed mobile scenarios,and can provide accurate services,in addition to avoiding the potential threat of service providers. |
