Research On Privacy-preserving Techniques Of Spatio-textual Skyline Queries

With the rapid development of mobile devices and mobile social networks,large amount of geographical location data are merged with traditional textual data,which result spatio-textual querying services based on both spatial proximity and textual relevance are widely applied in mobile social networks.To achieve flexibility and cost-savings,more data owners are motivated to outsource their data retrieval services to public cloud,which,however,may bring serious privacy issues.Through in-depth analysis of the privacy protection requirements of spatiotextual skyline queries in cloud environments,in this thesis,we define and study the problem of privacy-preserving spatio-textual skyline query processing in cloud environment,and propose privacy-preserving spatio-textual skyline querying approaches.To this end,we first present a privacy-preserving spatio-textual skyline query method based on linear scanning.In order to ensure the protection of spatio-textual data,sensitive information in spatio-textual skyline query requests and user privacy information during the query processing,we use Asymmetric Scalar-product-Preserving Encryption algorithm to encrypt such data.Based on the encrypted spatio-textual data objects and spatio-textual skyline query requests,a secure spatio-textual dominance calculation method is proposed by using the inner product preserving feature of the encryption algorithm,which allows to securely calculate spatio-textual dominance relationship for a pair of data objects over query requests with multiple locations.Through linear scanning the encrypted data objects,we utilize secure spatio-textual dominance calculation method to get spatio-textual dominance relationship of each pair of data objects and find the data objects that are not spatio-textually dominated by any other objects,which are considered as the result of privacy-preserving spatio-textual skyline queries.In order to satisfy the performance requirements of privacy-preserving spatio-textual skyline queries,we further propose a privacy-preserving spatio-textual skyline query method based on a secure index.An encrypted IR-tree is used as the query index of privacy-preserving spatiotextual skyline query and a secure spatio-textual dominance calculation method over index units is proposed.In this method,utilizing the distribution of spatio-textual similarities between query requests and index units,we improves the skyline query performance by pruning the index units that are dominated by any other objects or index units.Finally,through accessing the secure index level by level,based on the secure spatio-textual dominance calculation method,data objects that are not dominated by any other objects or index units can be found securely and efficiently,so that the privacy-preserving and efficient spatio-textual skyline query processing is achieved.Besides,for the above research works,we make a theoretical analysis on the security and computational complexity of the proposed methods.At the same time,over several real datasets,setting multiple groups of experimental parameters,we evaluate the performance of the proposed methods in the aspects of index construction costs and query response time.The experimental results show that the query efficiency of the proposed methods has been significantly improved.