大数据安全研究综述

随着人工智能、云计算、移动互联网和物联网等技术的融合发展,传统的基于边界安全域和基于已知特征库的网络安全防护方式已经无法有效应对大数据环境下新的安全威胁。通过对大数据环境下面临的安全问题和挑战进行分析,提出基于大数据分析和威胁情报共享为基础的大数据协同安全防护体系,将大数据安全技术框架、数据安全治理、安全测评和运维管理相结合,在数据分类分级和全生命周期安全的基础上,体系性的解决大数据不同层次的安全问题。基于该安全防护体系,分析了数据安全的关键技术及其目前的发展现状,并展望和分析了大数据安全领域面临的挑战。全面的分析和研究了大数据安全的威胁、政策、标准、方案、关键技术和挑战,对开展大数据安全建设和工程应用有重要参考意义。

A Survey of Big Data Security

With the integration and development of technologies such as artificial intelligence,cloud computing,mobile Internet,and IoT,the traditional network security protection methods based on border security domains and based on known feature libraries can no longer effectively deal with new security threats in the big data environment.By analyzing the security problems and challenges faced by big data,a collaborative security protection system based on big data analysis and threat intelligence sharing is proposed.By combining the big data security technical framework,data security governance,security evaluation and operation and maintenance management,the security issues at different levels of big data are systematically solved on the basis of data classification and full life cycle security.Based on this security protection system,the key technologies of data security and its current development status are discussed,and the challenges faced in the field of big data security prospected and analyzed.Finally,this paper comprehensively expounds and explores the threats,policies,standards,programs,key technologies and challenges of big data security,which has important reference significance for the development of big data security and engineering applications.