Research On Privacy Protection Based On LBS Service Of Mobile Users

In recent years,with the continuous development of communication technology and the continuous popularization of smart devices,people have entered a new era of smart information.Smart mobile devices have been closely related to people's lives.At the same time,related services are also rising,especially the location-based services(LBS)have also been widely used.It is undeniable that LBS brings convenience to people's lives.However,the user must report his current location information to the LBS service provider in order to obtain the required service.If the information falls into the hands of malicious opponents,users may face serious privacy threats.Therefore,it has both important theoretical significance and application value to research mobile user privacy protection methods based on LBS services.Efficient privacy protection mechanism is an important prerequisite for ensuring the continuous and vigorous development of LBS services.At present,it is difficult to overcome the single-point bottleneck problem with the method based on the central server architecture in the existing privacy protection methods.The method based on the P2P(Point-to-Point)architecture can avoid this problem,but it is not comprehensive enough to consider the credibility of collaborative users.Although these methods work to protect privacy to a certain extent,they still cannot cope with the disguise attacks of malicious attackers.Therefore,it is particularly important to provide comprehensive and efficient privacy protection methods for LBS services.This thesis focuses on two query methods based on LBS services: snapshot query and continuous query,and protects the privacy of single-point location privacy and continuous trajectory respectively.Aiming at location privacy,this thesis adopts a P2 P architecture to form an anonymous collaborative group with neighbor users to protect location privacy.For other members of the anonymous collaborative group,this thesis introduces blockchain,comprehensively considers incentive mechanisms and time-sensitive functions,and proposes mobile users trust management methods to standardize user behavior,and prevent malicious users from intruding into anonymous collaboration groups.This method has a good privacy protection effect,meanwhile it can resist malicious user attacks and attacks based on background knowledge.Aiming at trajectory privacy,this thesis adopts an independent architecture.A user can communicate directly with the LBS server.The user's mobile terminal adopts a rotation + offset method to generate k-1 similar trajectories with high similarity,which confuses the attacker and protects the real trajectory of the user.It is proved by simulation that this algorithm guarantees the authenticity of the generated trajectory,and has better privacy protection effect and performance.