Research On Fine-Grained Privacy Protection Data Aggregation Scheme In Internet Of Things Based On Edge Computing

With the rapid development of 5G and new communication technologies,the Internet of Things technology has been developed and applied rapidly,which has led to the rapid growth of the number of Internet of things terminal devices at the edge network.The massive raw data generated by these terminal devices at the network’s edge will cause a significant load on the network.The Internet of things model based on edge computing can well solve these problems.Edge computing can significantly reduce the computing and communication load and reduce data processing delay by deploying the edge server on the edge side of the network to provide services for the Internet of things terminal equipment nearby.However,edge computing also faces privacy threats.Data aggregation is an essential technology in edge computing.In edge computing-based data aggregation,the edge server collects and aggregates the real-time data of the terminal device and uploads the aggregated data to the cloud server for data analysis.Because the data collected by the terminal device may reveal the user’s sensitive information,privacy protection data aggregation based on edge computing has gradually become an important research point.How to provide more prosperous and more efficient data aggregation services to protect users’ privacy has become an urgent problem to be solved.Firstly,the existing privacy protection data aggregation scheme based on edge computing does not consider the fine-grained data aggregation based on user characteristics(such as longitude and latitude,height,etc.),so it can not get more fine-grained data.Secondly,for the Internet of things scenario with limited terminal equipment resources,the existing privacy protection data aggregation scheme is not lightweight enough and uses a large number of bilinear pairing calculations,which is not in line with the Internet of things application scenario with limited terminal equipment resources and unstable network environment.In addition,as a typical application of the Internet of things,smart grid has high requirements for the security and robustness of the system.However,most of the existing privacy protection data aggregation schemes only consider the privacy protection of the scheme and ignore the importance of fault tolerance.Therefore,the research work on privacy protection data aggregation in the above two Internet of things scenarios is as follows:(1)Aiming at the fact that the existing privacy protection data aggregation scheme in the Internet of things scenario with limited terminal equipment resources is not lightweight enough and does not consider the fine-grained data aggregation based on user characteristics,a finegrained and lightweight privacy protection data aggregation scheme based on edge computing Internet of things is designed.The edge server aggregates the data in a fine-grained manner according to the aggregation rules issued by the cloud center and the feature identifiers in the user data.In addition,our pairless signature scheme based on the elliptic curve has a faster signature and verification,and a shorter signature and protects the user’s identity privacy by assigning a pseudonym certificate list to the terminal device.Finally,the security and efficiency of the scheme are verified by security analysis and experimental analysis.(2)Aiming at the problem that the existing privacy protection data aggregation schemes in the smart grid scenario have poor fault tolerance and can not obtain fine-grained power consumption data based on user characteristics,a fine-grained,anti-collusion and fault-tolerant privacy protection data aggregation scheme based on edge computing outsourcing smart grid is designed.This scheme introduces service providers to provide more professional data analysis and reduce the load of power companies.In addition,by using the relative location list and secret value,the scheme can resist the collaboration of service providers and edge servers without sacrificing the system’s fault tolerance and supporting the secure billing function.In addition,the edge server performs fine-grained data aggregation on the power consumption data according to the encrypted aggregation rules and the encrypted user characteristic identification.Finally,the security and efficiency of the scheme are verified by security analysis and experimental analysis.