[1]徐胜超,宋 娟,潘 欢.基于 MapReduce 并行关联挖掘的网络入侵检测[J].计算机技术与发展,2021,31(06):123-128.[doi:10. 3969 / j. issn. 1673-629X. 2021. 06. 022]
　XU Sheng-chao,SONG Juan,PAN Huan.Network Intrusion Detection Based on Parallel AssociationMining of MapReduce[J].,2021,31(06):123-128.[doi:10. 3969 / j. issn. 1673-629X. 2021. 06. 022]
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基于 MapReduce 并行关联挖掘的网络入侵检测()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
31
期数:
2021年06期
页码:
123-128
栏目:
网络与安全
出版日期:
2021-06-10

文章信息/Info

Title:
Network Intrusion Detection Based on Parallel AssociationMining of MapReduce
文章编号:
1673-629X(2021)06-0123-06
作者:
徐胜超1 ; 宋 娟2 ; 潘 欢2
1. 广东财经大学华商学院 数据科学学院,广东 广州 511300;
2. 宁夏大学 宁夏沙漠信息智能感知重点实验室,宁夏 银川 750021
Author(s):
XU Sheng-chao1 ; SONG Juan2 ; PAN Huan2
1. School of Date Science,Huashang College,Guangdong University of Finance & Economics,Guangzhou 511300,China;
2. Ningxia Key Lab of Intelligent Sensing for Desert Information,Ningxia University,Yinchuan 750021,China
关键词:
云计算; 网络入侵检测; 关联数据挖掘; 映射-规约; 并行化
Keywords:
cloud computing; network intrusion detection; association data mining; MapReduce; parallelization
分类号:
TP393. 093
DOI:
10. 3969 / j. issn. 1673-629X. 2021. 06. 022
摘要:
随着海量大数据的出现, 关联数据挖掘算法需要新型计算模式来提高计算速度与运行效率。提出了基于 Map-Reduce 并行关联挖掘的网络入侵检测方法 Cloud-Apriori。 Apriori 是一种基于频繁项集的关联规则数据挖掘算法,Cloud-Apriori 是经 MapReduce 云计算并行化后的新算法。 Cloud-Apriori 利用开源的 Hadoop 分布式计算框架, 采用Hadoop 分布式文件系统存储海量数据;结合 MapReduce 的映射,规约操作,可以把关联挖掘的数据流和任务组成一个有向无环图,方便专业技术人员按照映射-规约的方式进行分布式计算的编程。 分析了基于 Map-Reduce 的并行关联挖掘的模块组成与实现过程。 Cloud-Apriori 利用 Kddcup 的案例数据和网络入侵检测这种大数据应用来仿真算法的效果。 实验结果表明:与存在的网络入侵检测算法相比,Cloud-Apriori 在检测精度、运行时间上有很好的优势。
Abstract:
With the emergence of massive big data,the association data mining algorithm needs a new computing mode to improve the calculation speed and operation efficiency. We propose a network intrusion detection based on MapReduce parallel association mining called Cloud-Apriori. Apriori is a data mining algorithm for association rules based on frequent item sets,and Cloud-Apriori is a new algorithm after the parallelization of MapReduce cloud computing. Cloud- Apriori uses open source Hadoop distributed computing framework and uses Hadoop distributed file system to store massive data. Combined with the mapping and protocol operation of Map-Reduce, the data flow and tasks of association mining can be formed into a directed a cyclic graph, which is convenient for professional and technical personnel to carry out the programming of distributed computing in the way of map-protocol. The design and implementation of the data mining model based on Cloud-Apriori is described and discussed. A serial of experiments are also done using Kddcup datasets and the intrusion detection processing of big data. Experiment shows that the overall detection effect and executing times of Cloud-Apriori are significantly better than the existing intrusion detection algorithms.

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更新日期/Last Update: 2021-06-10