Research On Track Privacy Protection Technology

In daily life,people often use location-based service Apps such as Meituan,Are you hungry,and Ctrip.These Apps greatly facilitate people's lives.People usually need to provide their own location information when using these Apps.When people use these apps to enjoy the corresponding services,they usually need to provide their own location information.This may lead to the risk of privacy information leakage,which needs to be protected by measures.For this reason,the industry has launched a series of exploration and research on trajectory location privacy protection.Some feasible methods,such as false data method,suppression method,generalization method and so on are proposed.In addition,some useful attempts have been made in the measurement of trajectory privacy protection and the structure of privacy protection system.However,most of the current trajectory location privacy protection schemes are aimed at ideal scenarios,which are difficult to resist background knowledge attack or continuous query attack.The author has carried out in-depth research on this,and made contributions in attack model,privacy protection system,access control model,privacy metrics and so on.The main research work in this dissertation includes:1.In order to make the proposed algorithm better resist the attacker's background knowledge attack,firstly,a false trajectory recognition scheme is proposed for the background knowledge,and this recognition scheme is used to determine whether the proposed algorithm can resist the background knowledge attack.This scheme judges whether the trajectory is a false trajectory based on the proportion of the time-reachable path in the trajectory.If the proportion is too high,the trajectory is judged to be a false trajectory.Then,by this scheme,the experimental attacks on the traditional false trajectory protection algorithm are made.The experimental results show that the traditional false trajectory generation algorithm can not effectively protect the trajectory information.2.For the existing false trajectory privacy protection schemes,in the process of generating false trajectories,background knowledge attacks are often ignored,and the similarity between the false trajectories generated by many trajectory privacy protection schemes and the real trajectory of the user is often insufficient.Starting from the movement mode of the user's trajectory,whether the request probability at a single point position on the trajectory is reasonable,whether two adjacent points on the trajectory are reachable in time,and the motion directionality of the trajectory,etc.,comprehensively consider the generated false trajectory,A privacy protection scheme for false trajectories is proposed.The experimental results show that compared with the traditional trajectory privacy algorithm,the proposed algorithm can protect the user's privacy information with lower computational cost,and greatly improve the practicability of the trajectory privacy protection system.3.In traditional k-anonymity method,it is difficult to search k-1 anonymous users in sparsely populated places or time periods,and it is easy to identify false tracks by continuous query attacks,thus reducing the security of real tracks.The author suggests the time cut-off method.The main idea is that given a time cut-off point,if the required anonymous user cannot be searched after the timeout,the false location is used to replace the required anonymous user.When the location server needs to query the location,the third-party anonymous server uses different pseudonyms to send query requests to the location server instead of real users.The security of the proposed trajectory privacy protection scheme is analyzed through experiments.The experimental results show that the scheme can effectively prevent continuous query attacks and solve the problem of generating anonymous users when there are few people.