Research On Incentive Mechanism And Privacy Protection For Vehicle Map Updating

With the development of artificial intelligence technology,Autonomous Vehicles(AVs)has gradually become a research hotspot.AVs can relieve the traffic pressure,and make the travel of the elderly and the disabled more convenient,which has brought great help to people’s life.However,AVs must access a large amount of data from the vehicle map in order to make safe and effective real-time control decisions.So,real-time map plays an important role in AVs navigation.Compared with the existing map updating methods,the real-time map updating method based on crowdsensing has lower cost and higher accuracy.However,in the process of map updating,this method will increase the risk of data and user identity leakage.How to ensure the confidentiality of uploaded data and the anonymity of users is a challenge in real-time map updating.Meanwhile,in the process of map update,the map service platform cannot recruit enough vehicle users to obtain sensing data due to lack of incentive mechanism.Therefore,how to motive more vehicle users to provide high-quality sensing data in the key for real-time map updates.This paper focuses on the privacy security and incentive mechanism design in the process of map updating.It first introduces the research background and significance of map updating in the field of AVs.At the same time,it also analyzes the characteristics and problems of the real-time map updating method based on crowdsensing.Second,it combines the related research.And it expounds the existing problems in incentive mechanism and pseudonym scheme,as well as the scheme for these problems.The main contributions are as follows:(1)In view of the user privacy and data security in the process of map updating,we propose a secure and efficient map update scheme for AVs(SEMU).In the SEMU,vehicle users can sign the sensing data and store the encrypted data in the vehicular fog node by using signcryption and proxy re-encryption technology.When the map company wants to access the data,the vehicular fog node sends the encrypted data to the server,and the server re-encrypts the data to the map company.At the same time,server cannot obtain any explicit information about the data.In addition,the aggregate signature technology is applied to reduce the computational overhead.Through the credit management of vehicle users,the reliability of data can be improved.Finally,security analysis shows that the scheme achieves data confidentiality,integrity,reliability,authentication and non-repudiation,and guarantees the anonymity and traceability of users.The simulation results illustrate that the proposed SEMU has the incentive,and it is efficient in terms of computational overhead.(2)In view of the participation level,completion quality,payment control and privacy security in the process of map updating,we propose a secure and privacy-preserving incentive scheme for reliable real-time map updates(SPIR).Specifically,under the condition of limited service platform budget and limited vehicle user’s ability,an effectiveincentive mechanism based on reverse auction is presented,which can solve two core problems: i.e.,payment control for map service platform and completion quality for vehicle users.Meanwhile,a payment system based on blockchain technology is designed to ensure the security of reward distribution.In addition,the security of incentive mechanism and protect the privacy of vehicle users.In the real time map update services,SPIR can guarantee data reliability.Both theoretical analysis and simulation results indicate that the proposed SPIR achieves near optimal benefits.