基于区块链的信息共享及安全多方计算模型

Information Sharing and Secure Multi-party Computing Model Based on Blockchain

在大数据背景下,数据信息隐私和可控性成为了关注点。现有的计算模式大多依赖于第三方机构,第三方的不可依赖性和对信息的掌控易导致信息的安全性无法得到保证,容易出现大量隐私问题。为解决此问题,文中结合区块链的特征和安全多方计算,提出了一种安全、高性能的共享及多方计算模型,使得用户能在自主控制数据的同时也能保证数据计算和共享的安全性。该方案首先以链上存储和链下存储相结合作为基础,在该存储环境下,利用代理重加密方式进行数据共享;然后使用改进的共识算法确保节点间的一致性,进而在MapReduce计算框架中使用改进的同态加密算法实现在无需解密隐私数据的情况下直接用密文进行数据处理和安全计算;最后对方案的正确性与安全性进行分析并进行实验仿真。分析结果及仿真结果表明,该模型在数据量较大时具有高性能的优点,且在运算效率方面有比较大的提升。

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.