Research On Privacy-preserving Query Processing Algorithm For Location-based Service In Cloud Data Environment

With the development of cloud service technologies,the mobile Internet industries are undergoing profound transformations.The application of the cloud service platform has remarkably improved the efficiency of mobile Internet products.For those products that use cloud service platform,users should outsource their dataset to the cloud service provider(CSP)that will lead to some security threats because of the sensitive data.Location-based services(LBS)play an important role in the mobile Internet industries,which provide great convenience to mobile users.In order to improve user's experience of location-based services,the LBS provider tends to outsource the dataset of Points of Interests(POIs)and execute the query process on the cloud platform that will improve the efficiency of query processing.However,the dataset of POIs collected by LBS has high business value and the query request issued by clients will reveal users' privacy such as location and preference.Therefore,it is necessary to construct a privacy-preserving query service for both LBS provider and terminal users in the cloud service environment with location-based services.Furthermore,when the LBS provider outsourced the POI set,it is difficult to determine whether the CSP has executed the query process correctly when the client issued a query request.So it is also necessary to verify the query result after querying.At present,there is a lot of research on the privacy-preserving query on location-based services,including geographic data transformation,private information retrieve,k-anonymity,etc.But in terms of location-based services,there are still many problems as following:1.Existing researches usually use Euclidean distance to measure the distance between the querier and POIs.However,it is not practicable in a real scenario in a road network model.2.Existing methods usually execute the query procedure based on the factor of distance.However,in a real scenario,it is necessary as well to do a query based on the factor of ratings.Existing methods cannot meet the requirement of the personalized query request.3.As the POI dataset been outsourced to the cloud,it is difficult to verify the query result to detect the CSP's misbehavior and check if the query results satisfy the condition in the query request.In order to address the problems above and meet the requirement of query processing in the cloud service environment for location-based service,this thesis constructs a privacy-preserving query algorithm in a cloud environment for location-based service.The algorithm uses the order-revealing encryption,homomorphic encryption,and computing result verification to construct a personalized privacy-preserving query method,including the following works:1.In order to combine the road network with query procedure,this thesis proposes a method of LBS query service over the road network in a cloud environment.When the CSP outsources the POI set,the POI data will be encrypted based on the road network with order-revealing encryption and homomorphic encryption.When a query request issued by the client,the query request will be preprocessed to construct a query trapdoor over the road network,which provides a secure query service in the cloud service environment.2.In order to deal with the misbehavior such as modifying in the cloud platform,this thesis proposed a verifiable LBS query service in a cloud environment.Based on query processing in the cloud platform,the verifiable modular exponentiation has been used to verify the POI data and user's preference parameters.Finally,this thesis compares the query algorithm with existing methods in the experiment.The experimental results show that the proposed method in this thesis can provide secure query service for LBS application in the cloud environment.