大数据分析下异构网络安全的关联算法研究

Research on Correlation Algorithm of Heterogeneous Network Security Based on Big Data Analysis

正以指数速度迅速膨胀起来的大数据给人们带来了方便,也带来了一些安全隐患,而保证大数据环境下的网络安全已成为当今社会的一个重要课题。文中从大数据时代发展现状入手,分析大数据时代的网络安全问题,并探讨相应的方法措施,以此来促进互联网的发展。针对大数据的查询分析复杂和大数据量的特点,通过分析面向大数据的异构网络安全监控的相关技术,对真实数据进行化简,清洗以及不断规划等一系列处理操作并得到核心分析数据库,构建了一个可以提供测试环境以及模拟实际攻击行为的集群实验环境。最终测试和验证大数据环境下异构化网络安全监控平台的不同分析算法,通过安全事件的关联和分布式序列图的模式等方式进行网络安全监控的整体态势分析,为大数据环境下的异构网络安全监控提供了一些思路,也为信息安全企业提供了一个分析大数据下隐含规律的参考模型。

Big data,which is rapidly expanding at an exponential rate,brings convenience to people and some security risks.However,it has become an important topic in today’s society to ensure the network security under the big data environment.Starting from the development status of the big data era,we analyze the network security in the big data era and discuss the corresponding methods and measures,so as to promote the development of the Internet.In view of the characteristics of complex query analysis and large data volume for big data,by analyzing the related technologies of heterogeneous network security monitoring oriented to big data,the core analysis database is obtained through a series of operations such as simplification,cleaning and continuous planning of real data,and a cluster experiment environment that can provide test environment and simulate actual attack behavior is constructed.Finally we test and verify different analysis algorithms of heterogeneous network security monitoring platform in big data environment.The overall situation analysis of network security monitoring is conducted through the association of security events and the pattern of distributed sequence diagram,to provide some ideas for heterogeneous network security monitoring under the environment of big data,and also provide a reference model for information security enterprises to analyze the hidden laws of big data.