基于海量日志的入侵检测并行化算法研究
发布时间：2018-09-17 16:57
【摘要】：随着计算机技术和互联网的迅猛发展,对海量日志进行分析并进行入侵检测就成为重要的研究问题。针对这一现象,提出在Hadoop平台下利用并行化的数据挖掘算法对海量的日志信息进行分析从而进行入侵检测,然后利用搭建好的Hadoop集群环境对其进行验证,对不同大小的日志文件进行处理,并与单机环境下对比,证明在该平台下进行入侵检测的有效性和高效性,同时实验证明如果增大集群中的节点数目,执行效率也会相应的提高。
[Abstract]:With the rapid development of computer technology and Internet, the analysis of massive logs and intrusion detection has become an important research problem. Aiming at this phenomenon, a parallel data mining algorithm based on Hadoop platform is proposed to analyze the massive log information to detect the intrusion, and then use the Hadoop cluster environment to verify it. The log files of different sizes are processed, and compared with the single machine environment, the effectiveness and efficiency of intrusion detection under the platform are proved. At the same time, the experimental results show that if the number of nodes in the cluster is increased, The efficiency of execution will be improved accordingly.
【作者单位】： 大连艺术学院;
【基金】：辽宁省职业技术教育学会2015—2016年度科研项目:高职院校智慧教育云计算辅助教学平台的构建与应用研究(LZY15531)阶段性成果之一
【分类号】：TP311.13;TP393.08
[Abstract]:With the rapid development of computer technology and Internet, the analysis of massive logs and intrusion detection has become an important research problem. Aiming at this phenomenon, a parallel data mining algorithm based on Hadoop platform is proposed to analyze the massive log information to detect the intrusion, and then use the Hadoop cluster environment to verify it. The log files of different sizes are processed, and compared with the single machine environment, the effectiveness and efficiency of intrusion detection under the platform are proved. At the same time, the experimental results show that if the number of nodes in the cluster is increased, The efficiency of execution will be improved accordingly.
【作者单位】： 大连艺术学院;
【基金】：辽宁省职业技术教育学会2015—2016年度科研项目:高职院校智慧教育云计算辅助教学平台的构建与应用研究(LZY15531)阶段性成果之一
【分类号】：TP311.13;TP393.08
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