Research On Dummy-based Location Privacy Protection Model And Algorithm

Location-based services(LBSs)allow users to connect with others based on their current locations.For example,people use their positioning devices to find out his/her location like restaurants,bars and stores that they visit.However,frequent and continuous accesses to the services expose users to privacy risk.A LBS provider might be able to collect private and delicate information about a user's choices and habits from the user's location,and it also raises concerns over potential intrusion into user location privacy.To protect location privacy,one typical approach is to cloak user locations into spatial regions based on user-specified privacy requirements,and to transform location-based queries into region-based queries.This paper focuses on issues related to privacy protection based on the nearest neighbor queries,the main work includes the following two aspects:1.Propose an improved dummy-based algorithm which can effectively deal with anonymous queries K nearest neighbors.This paper propose a privacy-protected KNN query anonymization method based on Bayesian estimation for Location-based services.Unlike previous dummy-based approaches,in the proposed method,the request to the LBS server doesn't contain the genuine user location,so it can't calculate whether meet the threshold condition of two location directly,but must to decision making by transition probability.In addition,the proposed method just requires the server returns the results the client needs.Further,this paper propose an effective search algorithm to improve the server processing.So it can reduce bandwidth usages and efficiently support K-nearest neighbor queries without revealing the private information of the query issuer.An empirical study shows that our proposal is effective in terms of offering location privacy,and efficient in terms of computation and communication costs.2.Propose an improved algorithm based on temporal locality for continuous proximity requests.For continuous proximity requests,one of typical anonymization methods is dummy-based approach.However,previous approaches have the slow server processing and long delay.This paper proposes an improved algorithm based on temporal locality for continuous proximity requests,instead of updating proximity relationship with repetitive computation.It can effectively improve the processing speed,reduce the response delay.An empirical study shows that the new algorithm has obvious advantages in efficiency compared with the previous dummy-based approach for continuous location-based proximity query requests.