Research On Privacy Preservation Techniques For Location And Trajectory

With the popular application of mobile Internet,smart terminal devices and GPS positioning technology,a large amount of trajectory data is generated for application in locationbased applications.However,providing location-based trajectory LBSs without additional privacy protection may expose users’ personal sensitive information and even their social relationships with each other.Therefore,the sharing and publishing of these location trajectory data cannot be supported by privacy preservation technologies,and the security of most privacy preservation technology models is based on certain background knowledge,which cannot provide perfect privacy preservation if the background knowledge has been mastered by attackers.Therefore,how to achieve secure sharing and publishing of location trajectory data has become an urgent problem to be solved.Privacy preservation technology refers to the technical system to realize data value mining under the premise of providing privacy preservation for data,which can realize the calculation of data in encrypted state or non-transparent state to achieve the purpose of privacy preservation for each participant.In summary,this thesis investigates the secure sharing and publishing of location trajectory data of single user and multiple users respectively,aiming to protect the privacy of users’ location trajectory data while enabling users to enjoy high quality web services.The main work and innovation points are as follows:(1)A blockchain-based privacy-preserving tracking scheme for the location trajectories of virus-infected individuals in a cloud environment is designed.First,the scheme combines localized differential privacy(LDP)technology and symmetric searchable encryption to achieve dual protection of positive patient privacy data.The decrypted results can resist collusion between different users.Second,a combination of LDP technology and CP-ABE enables finegrained access to shared keys by building access trees with trust attributes between users and data owners.CP-ABE reduces the strain on resource-limited devices by outsourcing encryption and decryption support.Then,a new Io T data management architecture is proposed by combining blockchain and cloud computing.By deploying smart contracts and introducing blockchain fairness mechanism to achieve fair execution for all parties,users can get the correct results without additional local verification,reducing the computational overhead on the user side.Finally,the scheme can effectively prevent the leakage of private data and achieve ciphertext retrieval.Its experimental results further prove the feasibility and practicality of the scheme.(2)A differential privacy-based privacy-preserving scheme for location-trajectory correlation in a cloud environment is designed.First,the scheme proposes a differential privacybased trajectory relevance privacy preservation mechanism for the trajectory correlation privacy problem among different users.The mechanism designs a Kalman filter-based trajectory prediction algorithm and uses differential privacy technology to protect the trajectory correlation and publish the user’s trajectory efficiently and securely.Secondly,the scheme proposes a trajectory prediction algorithm to predict and correct each location point,which can still maintain a stable error for time-honored real-time trajectories and improve the availability of location trajectory data.Then,the scheme proposes a personalized privacy budget allocation strategy that can better balance the noise error and prediction error and improve the utility of published trajectory data.Finally,the scheme has better advantages in three aspects: the degree of privacy preservation,data availability,and running time.(3)A review of the literature on research and progress in location-trajectory correlation differential privacy preservation techniques is summarized and presented.This thesis firstly introduces the concepts of differential privacy,global sensitivity,noise mechanism and Combination properties;secondly,it systematically researches and analyzes the locationtrajectory correlation privacy preservation techniques based on differential privacy,and further elaborates the privacy preservation methods in terms of time,space and spatio-temporal for the correlation preservation within a single trajectory,between two different trajectories and between multiple different trajectories under the differential privacy model.Finally,based on the comparative analysis of the existing methods,the future key research development directions of location trajectory correlation privacy preservation are proposed.