Research On Key Privacy-Preserving Techniques Of Spatial Network Queries

Recently,spatial network querying services have been widely employed in real-life applications.Outsourcing such services to the cloud platform will effectively save the local resources and service providing costs for data owners.However,directly outsourcing the services to the cloud may cause serious privacy concerns.Therefore,how to provide spatial network querying services on the cloud platform,while ensuring privacy protection is an important problem in this research field.To address this problem,this thesis focuses on the key privacy issues for spatial network querying services provided on the cloud platform,and presents several privacy-preserving methods for spatial network kNN query processing.In this thesis,we first present a privacy-preserving method for basic spatial network querying.The method implements the algorithm of basic secure spatial network kNN query processing based on the encrypted spatial network data and query requests.The algorithm first computes the kNN candidate sequences in Euclidean space,and then converts them into candidate sequences based on the shortest paths by pre-encrypted network distances.At last,the candidate sequences are securely updated by using Euclidean restriction,and we get the query result under privacy-preserving conditions.We further propose a privacy-preserving method of heuristic spatial network query in this thesis.The method implements a heuristic secure spatial network kNN query processing algorithm.It iteratively calculates optimistic estimate distances from the query node to the target node by using the homomorphic addition of Paillier crypstosystem.Then the heuristic search is performed on the spatial network according to the distance in the priority queue,and we obtain the query result under privacy-preserving settings.At last,we present a privacy-preserving method based on the partition tree for spatial network querying.The method proposes a secure index structure based on graph partitioning.With the secure index,such method executes a heuristic search within a priority queue to achieve the secure spatial network query processing effectively.Theoretical analysis shows security and complexity of the proposed methods,and experimental results on real data sets evaluate the query performance.