In recent years,with the continuous introduction of policies related to security,healthcare and environmental protection in China,the value of environmental data is increasingly important.However,the scientific management and secure sharing of environmental data in China is still in its infancy,and the amount of environmental data with privacy protection needs has increased a lot.However,there are many problems in data sharing,such as isolation of data centers and high risk of privacy leakage.Aiming at the environmental data sharing scenario and satisfying the privacy protection needs of the users'data cloud storage and cloud computing,the article combine blockchain with privacy computing to construct a data security management system based on fully homomorphic encryption and searchable encryption by using the national cryptography algorithms.Relying on blockchain deployment,cloud service storage and computing support,the system can realize two functions:machine learning supported by fully homomorphic encryption and searchable encryption.Based on a fully homomorphic encryption scheme,this article implemented a neural network prediction model and completed privacy computing on encrypted data.Moreover,this article realized a symmetric searchable encryption scheme,and the encrypted data can be stored in the cloud during the whole process,achieving ciphertext retrieval while protecting the privacy of query keywords.This system is deployed on the EOS blockchain with a weakly centralized third party,where the blockchain provides a reliable platform for data transactions and digital evidences,and the IPFS(Inter Planetary File System)provides a safe custody platform for encrypted data storage.As a result,the data circulation channels of all participants are effectively connected while ensuring both privacy and availability of encrypted data.
维普
万方数据