环保大数据在区块链中的隐私计算  

Privacy Computing in Environmental Big Data on Blockchain

作　　者：王南 袁也 杨浩然 文周之 苏明 刘晓光[1,2] WANG Nan;YUAN Ye;YANG Haoran;WEN Zhouzhi;SU Ming;LIU Xiaoguang(College of Computer Science,Nankai University,Tianjin 300350,China;College of Cyber Science,Nankai University,Tianjin 300350,China;State Key Laboratory of Public Big Data,Guizhou 550025,China4.;Key Laboratory of Data and Intelligent System Security,Ministry of Education,Tianjin 300350,China)

机构地区：[1]南开大学计算机学院,天津300350 [2]南开大学网络空间安全学院,天津300350 [3]贵州大学公共大数据国家重点实验室,贵州550025 [4]数据与智能系统安全教育部重点实验室,天津300350

出　　处：《信息网络安全》2024年第10期1515-1527,共13页Netinfo Security

基　　金：国家自然科学基金[62272253];天津市重点研发计划[19YFZCSF00900,20JCZDJC00610];公共大数据国家重点实验室开放课题[PBD2022-12]。

摘　　要：近年来,随着我国网络安全、医疗及环保相关政策的先后出台,环境数据的价值与日俱增。但我国对于环境数据的科学管理与安全共享仍处于起步阶段,具有隐私保护需求的环境数据数量急剧增加,但在数据共享上却面临数据孤岛化、泄露风险高等诸多难题。针对环境数据共享场景,为从根本上满足用户数据云存储和云计算的隐私保护需求,文章将区块链和隐私计算相结合,采用国密算法构建了一个基于全同态加密和可搜索加密技术的数据密态管理系统。依托区块链部署和云服务存储、隐私计算支持,系统可实现全同态加密机器学习和可搜索加密两种功能。文章基于全同态加密技术实现了神经网络预测模型,并完成了密态数据的云计算;同时,文章采用对称可搜索加密方案,支持数据在全程密态下的远程托管,能够实现密文检索并保护查询关键词的隐私。在保护隐私安全前提下,该方案有效打通了各方数据流通通道,保证数据可用不可见。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.

关 键 词：全同态加密 对称可搜索加密 区块链 机器学习 隐私计算 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]