Research On Privacy Protection Of Skyline Query For Mobile Cloud Location Service

Mobile cloud location services provide innovative solutions for information retrieval in mobile environments by integrating cloud computing and mobile communication technologies.Among these,Skyline queries,serving as a multidimensional data querying technique,play a crucial role in mobile cloud location services.Group Skyline queries aim to assist users in discovering target group information that meets their needs,composed of multiple target combinations from location information.Continuous Skyline queries,on the other hand,offer rapid querying of road networks based on users’ real-time dynamic locations.However,when using mobile cloud location services,users are required to provide query information to the cloud server,and service providers must also upload location information to the cloud.This may lead to the disclosure of personal privacy,exposing information that belongs to the service provider’s private assets to the cloud server.Existing privacy protection schemes for Skyline queries primarily focus on single-target data queries and queries based on users’ static locations,making it challenging to fully meet the diverse privacy protection needs of Skyline queries in mobile cloud location services.Therefore,the paper thoroughly analyzes the privacy protection challenges faced by Group Skyline queries and Continuous Skyline queries in mobile cloud location services and proposes corresponding solutions.(1)The paper introduces a privacy protection method for Group Skyline Query,named SSGQ,targeting combined location objectives.This method employs additive secret sharing techniques to protect both location information and query requests.Additionally,it proposes a secure twoparty group dominance protocol for calculating dominance relationships among groups.The cloud can utilize the secure group dominance protocol to obtain combined location objectives that meet the requirements and return the final results to the user through multi-round computations.To reduce the number of groups that need to be calculated in each round,a further proposal is made for a secure three-party group filtering protocol.This protocol can filter out dominated groups in a blinded manner.Security analysis indicates that this method effectively protects the privacy of location information and access patterns.The validity of the method is verified through simulation experiments.(2)The paper further proposes a privacy protection method for Continuous Skyline Query based on real-time dynamic locations,denoted as SCSQ.This method utilizes symmetric encryption and homomorphic encryption techniques to protect the privacy of road networks and query requests.It implements a secure dominance region partition protocol based on a two-hop table road network index to calculate dominance regions among location information.The cloud can use the secure dominance region partition protocol to locate the dominance region where the user’s current position is situated and return the final results through computation.To enhance query efficiency,a secure dataset filtering protocol based on a pruning strategy is introduced.This protocol can filter out location information that needs to be included in the dominance region partition.Finally,security analysis indicates that this method effectively protects the privacy of road networks and the queried user’s location.Simulation experiments demonstrate the practicality and efficiency of this method.