Network intrusion detection method based on machine learning

A network intrusion detection and machine learning technology, applied in machine learning, instruments, computer components, etc., can solve the problems of immature accuracy and detection speed

Active Publication Date: 2019-09-06
DONGHUA UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the network intrusion detection technology has developed to a certain extent, the accuracy and detection speed are not mature enough.

Method used

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  • Network intrusion detection method based on machine learning
  • Network intrusion detection method based on machine learning
  • Network intrusion detection method based on machine learning

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Embodiment Construction

[0066] In order to make the present invention more obvious and comprehensible, preferred embodiments are described in detail below with reference to the accompanying drawings.

[0067] like figure 1 As shown, the present invention provides a network intrusion detection method based on machine learning, which specifically includes the following steps:

[0068] 1. Data preprocessing.

[0069] Take 20% of the KDD99 dataset as the training set. Random sampling Since there are various types of data in the original data, it is necessary to perform symbol-value conversion and normalization of the data to change the features into the range of 0 to 1; due to too many redundant features, it has an impact on the final modeling , also affects the training speed; because the number of samples of some types is too small, it will bring great difficulties to the classification and recognition, so a small number of samples should be amplified.

[0070] The process of data preprocessing is a...

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Abstract

The invention relates to a network intrusion detection method based on machine learning. Use of conventional processing methods, such as: for example, in a data pre-processing stage carrying out symbol value conversion and normalization processing; artificially synthesizing samples with a small data volume by using an SMOTE algorithm, carrying out undersampling on the samples with the multiple data volumes by using a simple resample undersampling method, sorting the features by using an FCM clustering algorithm according to membership degrees, and selecting the features with high membership degrees as main features for extraction; in a model construction phase, firstly, classifying each large exception into a plurality of types of small exceptions by using kmeans clustering, establishing the four-layer nested XGboost model through establishment of the classification refinement on the XGboost model, and finally, explaining whether the better performance exists or not by comparing the trained optimal model with other models and comparing the detection rate and the false detection rate of intrusion detection.

Description

technical field [0001] The invention relates to a network intrusion detection method based on machine learning, and belongs to the technical field of network intrusion detection. Background technique [0002] Nowadays, the Internet has come to thousands of households, and the Internet has become more and more closely related to people's lives. The development of the Internet has promoted the economic and social development of the world, and the human society's dependence on the Internet has increased day by day. Then, while the information revolution brings specific benefits to human society, it also has some hidden dangers. Hacking incidents are not uncommon, and computer viruses continue to multiply and evolve. The challenges brought by these information security have brought huge hidden dangers to social security, national property, and people's livelihood security. In today's increasingly prominent network security problems, timely and effective detection of network int...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06G06N20/00G06K9/62
CPCH04L63/1416H04L63/1441G06F18/23213
Inventor 袁强方建安
Owner DONGHUA UNIV
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