Security Query Protocol In Location Based Services

With the rapid development of wireless communications and mobile devices with location capability,location-based services(LBS)have been extensively used in almost all social and business domains.To enjoy the LBS,the user needs to send the exact location and query content to the LBS provider.However,by collecting and analyzing a user's location and query content,the LBS provider can easily infer a lot of sensitive information of the user.In terms of privacy and efficiency,the existing work also has the following main limitations.First,they fail to preserve the location and content privacy simultaneously.Second,for range queries,they have problems with low query efficiency.In addition,in the face of frequent update of LBS data,the existing work cannot support index update operation.Therefore,how to design a secure and efficient privacy-preserving range query protocol in LBS is still a challenging issue.This paper focuses on privacy protection,query efficiency and index update under LBS.The main work includes the following two aspects:1)For privacy protection and query efficiency,we propose a secure and efficient privacypreserving range query protocol based on bloom filter.which satisfies the three requirements of the location and query content privacy protection,query efficiency and scalable index size.To achieve location and query content privacy,we adopt the prefix membership verification scheme to encode index elements and a bloom filter to store index elements.To achieve query efficiency and scalable index size,we propose a balanced dynamic binary tree structure called DBtree.To optimize query efficiency,we propose both the index element encoding optimization and traversal optimization scheme.Finally,we conduct extensive experiments and security analysis,which confirm the efficiency and security of DBtree.2)To solve query efficiency and index update issues,we propose a secure and efficient privacy-preserving range query protocol based on cuckoo filter.To protect privacy and query efficiency,we propose a balanced dynamic binary tree structure called DBtree.To improve query efficiency,we propose a query optimization scheme of DCtree.To support the updating of DCtree,an index updating algorithm of DCtree is proposed,which can dynamically handle the insertion,deletion and modification of data items.Finally,we evaluate our scheme both on the simulated and real-world datasets.Experimental results show that DCtree scheme is more efficient than DBtree scheme in index size and query efficiency.