摘要
随着数据中心的快速发展,数据的安全管理存在数据传输不可靠、数据丢失、数据泄露等方面的问题。为解决此问题,文章对大数据平台数据的安全管理体系架构进行设计,该架构包括数据安全采集层、存储层、使用层。数据安全采集层从数据分类、数据分级、敏感数据识别、数据脱敏、多类型加密机制5个维度保障数据安全。数据安全存储层从多维度数据安全存储机制、基于网络安全等级保护制度的安全评测两个维度保障数据安全。数据安全使用层采用细粒度访问控制、基于区块链的数据保护、基于联邦学习的数据共享、全过程安全审计4种技术保障数据使用安全。通过设计基于区块链的数据保护模型和基于联邦学习的数据共享模型,进一步提升数据安全管理体系架构的可靠性和可用性。
With the rapid development of data center,there are some problems in data security management,such as unreliable data transmission,data loss and data leakage.In order to solve this problem,this paper designs the data security management structure of Big Data platform,which includes data security collection layer,storage layer and usage layer.Data security collection layer guarantees data security from five dimensions:data classification,data layering,sensitive data identification,data desensitization and multi-type encryption mechanism.Data security storage layer guarantees data security from two dimensions:multi-dimensional data security storage mechanism and security evaluation based on network security level protection system.The data security usage layer adopts four technologies:fine-grained access control,block chain-based data protection,federal learning-based data sharing and whole-process security audit.By designing data protection model based on block chain and data sharing model based on federated learning,the reliability and usability of data security management structure are further improved.
作者
胡志达
Hu Zhida(China Telecom Corporation Limited Tianjin Branch,Tianjin 300385,China)
出处
《江苏科技信息》
2021年第13期25-28,共4页
Jiangsu Science and Technology Information
关键词
大数据平台
数据安全
区块链
联邦学习
Big Data platform
data security
block chain
federal learning
