Research On LBS Location Privacy Protection Based On K-anonymity

With the development of mobile communications,spatial location and geographic information systems,Location Based Services(LBS)has become the best service for today's mobile users.Users enjoy the service and left a large number of and service attributes,which can be used by attackers,in the network.An attacker can use this information to infer user's other sensitive information,resulting in a user's privacy disclosure.Therefore,LBS privacy protection has become a hot issue in the current society.The LBS is divided into two steps: the query submission and the result return.Considering the two steps,a location privacy protection scheme is proposed.The main research contents of the scheme are as follows:(1)Preprocessing of perturbed location generation.Although using a perturbation submission query has the advantage of being unable to link a single user and reducing calculate and communication overhead,selecting a simple perturbation makes the user to take on a higher risk of privacy disclosure.Therefore,a new algorithm is proposed to solve this problem.The algorithm uses the Hilbert Cloak algorithm to return the user in the anonymous region as the basic data for the perturbation.The choice of Hilbert Cloak is not only because of the advantages of its high flexibility and reciprocity,but also the experimental results show that in the classic k-anonymous technologies,its performance is better and more efficient.(2)Differential privacy guarantee for perturbation.If the attacker has enough background knowledge,the classic privacy protection technology cannot resist this background knowledge attack.Aiming at resisting the attack model,the method of dealing with the perturbation of differential privacy based on k average tree is proposed.Differential privacy has been proven to be the most effective privacy protection technology that ignores attackers' background knowledge,and experimentally proves that the error is within the allowable range.The distance between the perturbation and the exact location obtained using the perturbation generation algorithm is more reasonable and enhances the effect of privacy protection.(3)LBS query algorithm based on perturbation.In view of the shortcomings of the SpaceTwist algorithm,such as the poor precision of the returned result set and the high communication overhead,an improved SpaceTwist algorithm is proposed,which can not only improve the query efficiency,but also meet the requirements of k-anonymity.First,the query decision condition requires that the demand space radius be greater than the distance between the perturbation and the exact location,to improve query efficiency;secondly,the query termination condition requires that the number of users in the demand space must be greater than or equal to k,then the algorithm satisfies the k-anonymity,thus confusing the opponent.The overall performance of the proposed scheme is verified by experiments.The results show that the proposed scheme can not only resist the attack of several existing privacy attack models,but also guarantee the execution efficiency and the accuracy of the result set.