Network intrusion detection method for parallel AP cluster based on MapReduce

A technology of network intrusion detection and AP clustering, which is applied in the field of network security and can solve problems such as slowing down of calculation speed and inoperability

Inactive Publication Date: 2015-02-25
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0002] With the rapid expansion of network traffic, massive data processing and calculation have become common problems in intrusion detection. Many traditional intrusion detection methods are often only suitable for small-scale data processing. When the amount of data increases, they are often and slow down or even stop running

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  • Network intrusion detection method for parallel AP cluster based on MapReduce
  • Network intrusion detection method for parallel AP cluster based on MapReduce
  • Network intrusion detection method for parallel AP cluster based on MapReduce

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[0045] The present invention will be further described below in conjunction with the drawings.

[0046] Reference Figure 1~Figure 8 , A network intrusion detection method based on MapReduce parallel AP clustering, which speeds up detection by reducing the amount of calculation of network intrusion detection classifier data samples. First, the parallel AP clustering based on MapReduce is used to compress the number of intrusion detection samples and reduce the number of intrusion detection samples. The calculation amount of training samples is used in the classifier, and then the compressed data samples are used to achieve high-speed detection performance through KNN or SVM classifiers and maintain good detection accuracy.

[0047] According to the parallelization process of the AP algorithm, the main steps of the AP clustering parallelization method disclosed in the present invention include: MapReduce parallelization for similarity matrix calculation, MapReduce parallelization fo...

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Abstract

The invention provides a network intrusion detection method for a parallel AP cluster based on the MapReduce. The detection method includes the following steps that firstly, intrusion detection sample data is preprocessed, and numeralization and normalization of feature data are finished; secondly, the number of intrusion detection samples is compressed through the parallel AP cluster based on the MapReduce; thirdly, efficient detection is achieved through the compressed data samples by means of a KNN or SVM classifier. According to the network intrusion detection method for the parallel AP cluster based on the MapReduce, good expansibility is achieved in the data sample processing process, mass data samples can be effectively compressed, the detection speed is increased, and the detection accuracy is improved.

Description

Technical field [0001] The invention relates to the technical field of network security, in particular to a network intrusion detection method. Background technique [0002] The rapid expansion of network traffic and massive data processing and calculations have become common problems in intrusion detection. Many traditional intrusion detection methods are often only suitable for small-scale data processing. When the amount of data increases, they are often due to the increase in the amount of calculation. And the speed slows down or even cannot run. Summary of the invention [0003] In order to overcome the disadvantages of the existing network intrusion detection methods that the detection speed is slow and the detection accuracy is lower when the amount of data increases, the present invention provides a MapReduce-based parallel AP clustering that improves the detection speed and higher detection accuracy when the amount of data is large. Network intrusion detection method. [...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06
CPCH04L63/14
Inventor 陈铁明张旭
Owner ZHEJIANG UNIV OF TECH
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