Attack program identification method based on vulnerability attack database and decision tree

A program recognition and database technology, applied in character and pattern recognition, electrical digital data processing, instruments, etc., can solve problems such as potential safety hazards, affecting the classification accuracy of classification models, and errors in detection results, to improve performance and strengthen minimum redundancy. redundancy, and the effect of improving the recognition performance

Pending Publication Date: 2021-10-01
JIANGSU UNIV
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Problems solved by technology

In addition, various applications in the network emerge in an endless stream, which facilitates our life, but also brings many network security and network management problems, and there are various vulnerability attacks and malicious traffic in the network, which greatly threatens network security.
At present, when identifying attack programs, the most common method is to divide the data set into a training s

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  • Attack program identification method based on vulnerability attack database and decision tree
  • Attack program identification method based on vulnerability attack database and decision tree
  • Attack program identification method based on vulnerability attack database and decision tree

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Embodiment Construction

[0042] The present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be noted that the described embodiments are intended to facilitate understanding of the present invention, but do not limit it in any way.

[0043] The purpose of the present invention is to provide an attack program identification method based on a vulnerability attack database and a decision tree for attack programs in network traffic, which effectively realizes the classification and identification of attack programs, and conducts sufficient experiments to prove the feasibility of the method sex and effectiveness. Specifically:

[0044] Step 1, build a network traffic-oriented vulnerability attack database;

[0045] Step 2, preprocessing the data set of the attack program to be detected to obtain a higher quality and more representative data set;

[0046] Step 3, select key feature subsets in the vulnerability attack database and the attack...

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Abstract

The invention provides an attack program identification method based on a vulnerability attack database and a decision tree. The method comprises the following steps: step 1, constructing a vulnerability attack database facing network traffic; step 2, preprocessing a to-be-detected attack program data set to obtain a data set with higher quality and stronger representativeness; step 3, selecting key feature subsets in the vulnerability attack database and the attack program data set to be detected through a secondary feature selection method based on principal component analysis; step 4, training the key feature subsets selected in the vulnerability attack database by using a fast decision tree algorithm to construct a classification model; and step 5, completing the identification of attack programs according to the results of the step 3 and the step 4.

Description

technical field [0001] The invention belongs to the technical field of network flow attack programs, and relates to an attack program identification method based on a vulnerability attack database and a decision tree. Background technique [0002] Today's society is developing rapidly, and the Internet has become one of the most important information technologies. As the network scale continues to grow, network traffic data also shows an explosive growth trend. In addition, various applications in the network emerge in an endless stream, which facilitates our life but also brings many network security and network management problems, and various vulnerability attacks and malicious traffic in the network greatly threaten network security. At present, when identifying attack programs, the most common method is to divide the data set into a training set and a test set, train the training set to form a classification model, and then identify the test set. This method will vary ...

Claims

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Application Information

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IPC IPC(8): G06F21/57G06K9/62
CPCG06F21/577G06F18/2135G06F18/22G06F18/214
Inventor 蔡赛华陈锦富秦松铃张翅陈海波
Owner JIANGSU UNIV
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