Researsh On Optimization Of Hyperledger Fabric Consensus Mechanism For Epidemic Investigation

Since 2020,the outbreak of novel coronavirus has triggered a global public health crisis.The virus can spread through airborne droplets and close contact,causing severe respiratory illness and death.The epidemic has had a serious impact on the global economy and society.Although the new crown virus epidemic has passed more than half a year,it still has a profound impact on the world.Communicating epidemic-related information to the public in a timely manner can effectively reduce public panic and curb the development of the epidemic.This paper starts with the development of the epidemic situation in my country,and aims at the characteristics of openness,transparency and no human tampering of the epidemic situation data,introduces blockchain technology,and studies the blockchain cons.ensus optimization method for the management of the epidemic situation,and provides information for the management of the epidemic situation.Knowledge and technical support.The research content of this paper includes the following three aspects:Firstly,aiming at the security and privacy protection of my country’s new crown pneumonia epidemic data,and in order to ensure the confidentiality and integrity of the epidemic data,a verifiable random function based on the elliptic curve public key cryptographic algorithm SM2 is proposed,and passed Randomly select endorsement nodes to enhance data security.The algorithm uses SM2 as an encryption algorithm,which can effectively guarantee the confidentiality and integrity of data during transmission.At the same time,a verifiable random function is used to randomly select endorsement nodes to ensure that the selected nodes are impartial and verifiable,and to prevent data from being maliciously tampered with or stolen.Finally,the epidemiological surv ey data are summarized according to certain rules to ensure the confidentiality and integrity of the data.This algorithm can effectively improve the security of epidemic flow survey data and protect the privacy and rights of users.Secondly,aiming at the real-time nature of my country’s epidemic situation survey data and the limitations of traditional consensus algorithms in dealing with high-speed data processing,an improved PBFT consensus algorithm based on regional division,GR-PBFT(Improved PBFT Consensus Algorithm for Geographical Division).The algorithm uses blockchain technology to establish a decentralized trust mechanism between network nodes.At the same time,by grouping nodes according to geographical location,the scope of message broadcasting is reduced,and consensus efficiency and real-time performance are improved.In the processing of epidemic epidemiology data,the algorithm can collect and verify data from various places more quickly,and achieve rapid consensus and data synchronization.In this way,the algorithm can adapt to the needs of different regions and network environments,improving its applicability and flexibility.Finally,an experiment is designed,and the experimental results show that the improved PBFT consensus algorithm GR-PBFT based on regional division is especially suitable for the real-time data processing scenario of the epidemic situation.Thirdly,designed and implemented a Fabric federated chain-based epidemic flow transfer system.The development framework of the system is defined,and the module design,architecture design,use case design,and activity design of the system are briefly described.The relevant functions of the outbreak flow system are demonstrated.This includes the data information query function and the flow data query function,etc.Finally,the system is tested for functionality,and the test results show that the system can complete the flow and query of the epidemic data,and at the same time can ensure the authenticity and reliability of the data on the blockchain.