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Semi-supervised classification intrusion detection method based on ensemble learning

An integrated learning and intrusion detection technology, applied in the field of network security, can solve problems such as not being able to meet the user's network security requirements, and achieve good recognition, high recall and accuracy, and excellent performance

Pending Publication Date: 2020-12-22
CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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AI Technical Summary

Problems solved by technology

Only relying on traditional security measures such as intrusion detection systems can no longer meet users' requirements for network security.

Method used

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  • Semi-supervised classification intrusion detection method based on ensemble learning
  • Semi-supervised classification intrusion detection method based on ensemble learning
  • Semi-supervised classification intrusion detection method based on ensemble learning

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Embodiment Construction

[0064]The following describes the specific embodiments of the present invention to facilitate those skilled in the art to understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art,

[0065]As long as the various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious.

[0066]As you can see, all inventions and creations that use the concept of the present invention are protected.

[0067]Such asfigure 1As shown, a semi-supervised classification based intrusion detection method based on ensemble learning includes the following steps:

[0068]S1. Use Generative Adversarial Network (GAN) to generate more U2R datasets to improve the detection rate of this type of attack

[0069]S2. Use the generated data set and 10% of the KDD-NSL data set to combine to generate a data set Dl

[0070]S3, use data set DlT...

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Abstract

The invention discloses a semi-supervised classification intrusion detection method based on ensemble learning, and the method is characterized in that a TSVM algorithm is used as a semi-supervised classification algorithm, and the method comprises the steps of firstly training an initial SVM for an original mark data set, marking an unmarked sample through employing a learner, and retraining theSVM based on the marked sample; and finally obtaining a group of expanded mark data. The LightGBM framework is trained by utilizing the original mark data and the expanded mark data to serve as a classifier of ensemble learning, and various attack types can be effectively distinguished. According to the invention, the better performance can be obtained by only needing a small amount of mark data,and particularly for an attack mode with lower occurrence frequency, more data is generated by adopting the GAN for training. Compared with a traditional intrusion detection system, the intrusion detection system has high accuracy and can make a response in time.

Description

Technical field[0001]The invention relates to the field of network security, in particular to an intrusion detection method based on integrated learning semi-supervised classificationBackground technique[0002]With the continuous improvement of my country's high-tech level, computer technology and network technology have been further optimized and improved. But what followed is that network attacks continue to emerge, and network attack methods have become more and more complex. Symantec's 2018 Internet Security Threat Report pointed out that 1 out of 10 URLs analyzed is malicious. And with the rapid development of cloud computing, security mistakes made on personal computers are most likely to occur in the cloud. A misconfigured cloud workload or storage instance can cost the cloud service company millions of dollars. In May and June 2017, the ransomware "WannaCry" and "Petya" launched attacks in more than 10,000 organizations in more than 150 countries. In China, through the "Repor...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/55G06K9/62G06N3/04G06N3/08
CPCG06F21/554G06N3/08G06N3/045G06F18/214G06F18/241G06F18/24323
Inventor 肖洪光陈浩
Owner CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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