Research On LBS Privacy Protection

Location-based services bring convenience to people's daily lives.Near-neighbor queries,as the basic services of location services,are widely used in various scenarios.However,how to protect themselves when users use nearest neighbor services privacy security has become an important issue to be solved.As the number of users and data access increases,and the cost is limited,the cloud service model will become the first choice of service providers.However,existing privacy protection technologies often cannot be applied to cloud service models or are computationally complex and inefficient.After analyzing the characteristics of various existing location privacy protection technologies,this thesis presents a corresponding solution for single-point location query and linear region query based on cloud service architecture model in European space.The specific work is as follows:1.Aiming at the problem that the single query point range search efficiency is low by using encryption technology,a secure nearest neighbor point of interest query scheme with semantic query information is proposed.The core idea is to encrypt the user's query location and semantic query conditions,and the cloud server uses the ciphertext calculation to return the points of interest that satisfies the condition.The method well protects the user's query location information,and can be filtered according to semantic conditions.The encryption and decryption process is simple in calculation and has good query efficiency and quality.2.A fast query scheme for linear neighborhood neighbors is proposed.Firstly specifies the query line segment by the user,and after adding the index point and encryption processing,it sends it to the cloud server.The cloud server uses the ciphertext to calculate the positional relationship between line segments and rectangles according to the conditions,and finally returns a collection of points of interest to meet the requirements.By adding additional index points to the map search tree,the method reduces the calculation steps in the query and has higher query efficiency than the original method.3.A shortest path query method suitable for the cloud service environment is proposed.The user's query information privacy is protected by adding virtual mirror nodes to the map data,and a feature of querying a certain range of interest points near the designated road is obtained.