Research On Privacy Protection Of Crowdsourcing Application In Internet Of Vehicles

With the rapid development of vehicle-mounted terminals,the ability of vehicles to collect and process data has been greatly improved,making crowdsourcing,an emerging application mode,gradually become popular in the Internet of Vehicles.In the Internet of Vehicles crowdsourcing application,vehicles can not only participate in crowdsourcing tasks and contribute to the collection of service data,but can also initiate data requests on demand to obtain service data.However,the risk of privacy leakage during data col-lection/request has severely hindered the widespread application of Internet of Vehicles crowdsourcing.When vehicle users collect data/requests,they generally include user-related private information,such as identity,location,and query content.The leakage of private information will make it easy for attackers to infer the behavior patterns of vehi-cle users and obtain the users’ true intentions.Therefore,the leakage of privacy leads to poor vehicle user experience and reduces vehicle user participation in crowdsourced ap-plications.In order to solve the privacy problem of the crowdsourcing application of the Internet of Vehicles,this thesis first establishes the corresponding data transmission model and attack model,and then proposes the corresponding privacy protection plan.The main research contents are as follows:(1)Aiming at the scene of vehicle users collecting data and requesting data in crowd-sourcing applications,two data transmission models are established,namely,data collec-tion model and data request model.Analyze the related privacy issues involved in the operation of the two models,and then propose the corresponding attack models.(2)Aiming at the leakage of user identity and location privacy in data collection sce-narios,this thesis proposes a privacy protection scheme based on data aggregation and batch authentication.First of all,in order to ensure the privacy and availability of data,this thesis selects homomorphic encryption algorithm for encryption processing? then,us-ing the nature of homomorphic encryption,the encrypted data is aggregated to effectively reduce the calculation and communication overhead of the roadside unit.In addition,for the authentication between data interaction entities,the solution adopts bilinear pairing technology to realize batch authentication of identities,reducing authentication overhead.Finally,simulations verify that the scheme can protect the privacy information of the iden-tity and location of vehicle users when collecting data.(3)Aiming at the privacy leakage of user location and query content in data request scenarios,this thesis proposes a privacy protection scheme based on differential privacy and generalization of points of interest.The solution firstly performs random disturbances to meet the differential privacy of the user’s location to achieve a balance between location privacy protection and service quality? at the same time,a generalized method is used to obscure the content of the user’s interest points to ensure the privacy of the user’s query content.Finally,simulations verify that the scheme can protect the privacy of the vehicle user’s location and query content when requesting data.