Abstract: Under the background of big data,the control and privacy of data information have become a concern.However,existing computation models mostly rely on the third-party institution.Because the incompliance and the information control of the third party cause that information security cannot be guaranteed,more privacy problems appear.To solve this problem,this paper constructed an information sharing and secure multi-party computing model with high performance and security combining the blockchain with the secure multi-party computation,which enables users to control the data autonomously while ensuring the security of data information computing and sharing.This scheme firstly combines the on-chain storage with the off-chain storage.In this storage condition,proxy heavy encryption is used for data sharing and improved consensus algorithm is used to ensure the accuracy of nodes.Then,based on the MapReduce parallel computing framework,an improved homomorphic encryption algorithm was put forward for data processing and secure computing in cipher without decrypting the privacy data.Finally,the correctness and the security of the scheme were analyzed,and the experimental simulation was carried out.The analysis results and experimental results show that this scheme has high performance when dealing with big data and has a great improvement in operational efficiency.

Key words: Blockchain, Consensus algorithm, Homomorphic encryption, MapReduce, Secure multi-party computation