Research On Privacy-preserving Skyline Query Algorithms

The rapid development of precise positioning technology promotes the development of Location Based Services(LBS)industry.In practical applications,users’ location and data security are often confronted with great challenges due to factors such as dishonesty to third-party Location based service providers or other potential malicious attacks.Privacy protection of Location based services has also become one of the research hotspots in recent years.Skyline query is a very important kind of data query method for high-dimensional data,it can return desirable data records that user may be more interested in.Through an in-depth analysis of the privacy protection requirements of Skyline query based on location service and seeking a balance between privacy protection and query efficiency,this thesis defines and studies the problem of privacy-preserving skyline queries for location-based services,the main works are summarized as follows:First,this paper defines the user privacy protection intensity in different data dimensions.Second,a privacy protection algorithm based on square hidden area is proposed,quadrant skyline and dynamic skyline queries are performed on the pre-processed user query request with BNL and BBS algorithms,which not only effectively hide the user query location but also realize fast query.Finally,privacy-preserving quadrant skyline and dynamic skyline algorithms based on cubical hidden region are proposed for 3-dimensional space and the performance of the proposed algorithms on data sets with different data distributions are verified.Through theoretical and experimental analysis,we show that the proposed methods can effectively protection user’s location privacy,and can make a tradeoff between the protection level of user’s location privacy and query processing efficiency.