Application Research On Data Sharing Of Stroke Clinical Research Based On Blockchain

With the advancement of science and technology and the development of medical informatization,the large-scale use of medical data among clinical researchers has put forward the requirements for sharing clinical research data.Traditional data sharing mainly adopts a centralized method.The data is controlled by a single party and shared to multiple parties.Nowadays,with the increasing amount of data,various kinds of rich information of human society are stored in the data.The centralized data sharing method has serious problems.The potential safety hazards,and the resulting consequences are unimaginable.In recent years,blockchain technology has continued to develop and has become a popular technology of social concern.The technology’s decentralization,tamper-proof,encryption,and traceability characteristics can ensure the security of data.Blockchain technology has become an effective means to solve the problems of traditional data sharing centralized methods.In this context,in order to further promote the effective and safe conduct of clinical research data sharing and ensure that clinical researchers use large amounts of data more conveniently and quickly,this article is based on the background of the China Stroke Center Alliance,based on blockchain technology and a fully homomorphic encryption scheme.The clinical research data sharing of stroke disease establishes a model,design process,design sharing plan and implement it.The main research contents of this article are as follows:(1)Analysis of the main problems faced in the data sharing of clinical studies of stroke.This article analyzes the value of stroke clinical research data to obtain the role and significance of data sharing,and analyzes the current status of stroke data sharing,analyzes the existing problems of the existing model from all aspects of business scenarios and technical solutions,and at the same time Combining the common problems existing in the process of medical data sharing,the technical and management difficulties in the sharing of stroke clinical research data are analyzed,and the problems to be solved in this article are pointed out.(2)Construction and research of data sharing model for stroke clinical research.First,it analyzes the application scenarios of the stroke clinical research data sharing model proposed in this article,and establishes a stroke clinical research data sharing model based on the storage nodes of medical institutions at all levels and the blockchain(consortium chain and private chain)to ensure that the clinical research data is from The whole process from generation to sharing to use is safe.Propose the PoW-FHE model,which uses blockchain and its workload proof consensus mechanism,combined with fully homomorphic encryption to carry out the internal plan of stroke clinical research data sharing,and at the same time verifies the rationality of the plan,and is targeted for fully homomorphic encryption Optimally design.Design the shared external scheme,establish a sharing user’s authority management system in the blockchain,apply fully homomorphic encryption to smart contracts,and prevent privacy and security issues in the process of data sharing in the form of electronic contracts.The design is aimed at The internal and external network security access design of the original data storage node prevents data from being illegally destroyed before and after sharing,and prevents a node from illegally accessing stroke clinical research data in the blockchain due to external network attacks.(3)Realize a data sharing plan for stroke clinical research.This article uses real clinical research data to conduct experiments to achieve consistent calculation results of the fully homomorphic encrypted cipher text of stroke clinical research data,and realize stroke clinical research data to be shared in the blockchain,and it is concluded that the same data source is the case,The use of this sharing scheme for data sharing efficiency is better and its data sharing efficiency will be affected by the number of nodes.In addition,the safety is analyzed,and relevant implementation recommendations are provided for the sharing of stroke clinical research data.