大数据环境下的安全审计系统框架  

Security Audit System Framework in Big Data Environment

作　　者：丁文超[1] 冷冰[1] 许杰[1] 严丽娜[2] 

机构地区：[1]中国电子科技集团公司第三十研究所,四川成都610041 [2]西安通信学院信息安全系,陕西西安710106

出　　处：《通信技术》2016年第7期909-914,共6页Communications Technology

摘　　要：安全审计技术在现代安全防护系统中占有重要地位,但面对现代大数据环境,传统的安全审计技术对数据的有效管理、快速检索以及数据分析都会面临诸多较难克服的问题。简要介绍现有的Hadoop、Spark等主要大数据平台,针对传统安全审计技术无法处理大数据的问题,运用现有的大数据技术,给出大数据安全审计系统的设计思想,最终设计出大数据环境下的安全审计系统框架,并介绍框架中每一部分的作用与处理步骤,以满足大数据环境下的安全审计需求。Security audit technology plays an important role in modern security protection system. However,traditional security audit technology and effective management of data, fast retrieval and data analysis would be faced with many difficult problems in modern big data environment. Major data platforms are briefly described, such as Hadoop and Spark, and aiming at the problem that traditional security auditing technology cannot handle big data, the existing big data technology is applied to proposing the design idea of big data security audit system. Finally, the framework of security audit system in big data environment is designed, the role and process in each part of the framework also given. The framework can meet the needs of security audit in big data environment.

关 键 词：安全审计 大数据 数据挖掘 SPARK 

分 类 号：F239.2[经济管理—会计学]