Research On Privacy Protection Method Of Location Service Trajectory In Fog Computing

Due to the rapid development of Internet of Things application technology and wireless network communication technology.the application of location based service(LBS)for mobile user terminals is more wide,so data information such as user location and movement trajectory will be generated in large quantities.These users' personal privacy information is also in danger of leaking.The traditional location trajectory privacy protection relies mostly on the third party trusted(TTP)centralized anonymous server and the privacy protection scheme of the user terminal without centralized anonymous server.the TTP centralized anonymous server is easily concentrated and poses a performance bottleneck.Based on the user terminal scheme,the communication overhead between users is relatively large,and the user is not trusted problem.For the problems faced by TTP centralized anonymous server and user terminal based solutions,we designed a trajectory privacy protection scheme based on fog computing.The main research contents of this scheme are as follows:(1)Trajectory privacy protection method based on fog computing in location service.In order to protect the privacy information such as user trajectory in the location service,we designed a Trajectory Rotation Translation(TRT)algorithm to protect the user's trajectory privacy information in the architecture based on fog computing.Fog computing is an effective extension of some functions of cloud computing,and generally has local storage and computing capabilities at the edge of the network.In this paper,the fog server is used to replace the traditional TTP anonymous centralized server,which solves the performance bottleneck and concentrated attack problem caused by the centralized server in TTP.The problem of communication overhead between users and user untrustworthy based on the user terminal scheme can also be effective avoid.Then through the fog server to complete the designed TRT algorithm to achieve k anonymity of the user trajectory.The simulation analysis shows that the algorithm can effectively enhance the protection of private data such as user location and mobile trajectory.(2)Multiple fog cooperative trajectory privacy protection method based on graph division.First,we use the Voronoi diagram to divide the spatial region,and then arrange a certain number of fog servers in the divided regions.According to the division of the graph,the user's area is divided into clear area and non-clear area.After comprehensive analysis,a Bidirectional Incremental Nearest Neighbor(BINN)algorithm is designed.When the user is in the range of a fog machine,the user position k within the scope of the fog server is anonymous using the BINNalgorithm.The user moves at the different time to form the user's trajectory information,and thus designs a Multiple Fog Cooperative(MFC)trajectory k anonymity algorithm.Each fog server uses the MFC algorithm to complete the k anonymity of the user trajectory according to the privacy protection requirements of the user,thereby protecting the user's trajectory privacy information.Experimental results show that the algorithm not only improves the user anonymity efficiency in the process of query location service,but also effectively reduces the burden of the LBS central server,and is a method for efficiently protecting private data such as user location trajectory under a novel architecture.