Research On Location Privacy Protection Of IoT Devices Based On Anonymity

Internet of Things(IoT)technology has been widely used in various fields of society in recent years.The endless variety of Io T devices not only further promote the development of Io T,deepen the connection between Io T and people's daily work and life,but also play an important role in the emerging fields such as autonomous driving,robot,intelligent medical and so on.In the process of some Io T devices carrying out various automated tasks such as transportation or reconnaissance,it is sometimes necessary to dynamically plan the route temporarily.By submitting query information,devices can obtain the specific situation of the surrounding environment,and then analyze the required resources or docking location.Once the location data of these devices is obtained by attackers,it may lead to serious security threats and economic loss.In order to protect the location privacy of the device,it is necessary to hide its real location when the device submits the query information,but this may make the device unable to obtain the expected query service.Therefore,the difficulty and focus of device location privacy protection lies in the premise of protecting device location privacy,while taking into account the quality of query service.Many existing methods can only solve the security problem of location privacy under instantaneous query,but cannot prevent the leakage of location privacy under continuous query,and cannot resist the attackers with background knowledge.To solve these problems,this thesis takes the Internet of Things as the background,mainly uses the anonymity method to study the location privacy protection of devices under instantaneous query and continuous query.The main research work of this thesis is as follows:Aiming at the problem that traditional privacy protection schemes cannot effectively resist background knowledge attacks,a secondary anonymous location privacy protection scheme based on differential privacy is proposed.This scheme is based on the analysis of the properties and characteristics of differential privacy,meanwhile,it considers the combination of k-anonymity and differential privacy technology.The enhanced DLS algorithm is selected in the scheme,and the multi-objective optimization of entropy and distance is taken to generate the dummy position,so as to obtain the first anonymous result set.Then,Laplace noise mechanism is used to add noise to the location data of the first anonymous result set,so that the algorithm can satisfy the differential privacy and realize the second anonymity.Then,aiming at the contradiction between privacy and query quality in location privacy protection,the Stackelberg game model is proposed.Finally,a heuristic solution is proposed for other types of attacks that exist in the real environment.Experimental results show that the proposed scheme can make the dummy location diffuse as much as possible under the premise of privacy protection,and the operating speed is significantly improved.Through the experimental adjustment,the best balance between privacy and query accuracy is also achieved.