Unlock instant, AI-driven research and patent intelligence for your innovation.

Method, device and storage medium for training classifier based on sample features

A sample feature and classifier technology, applied in the field of network security, can solve the problem of low classifier performance, and achieve the effect of improving classifier performance and reducing feature redundancy.

Active Publication Date: 2021-11-16
COMP NETWORK INFORMATION CENT CHINESE ACADEMY OF SCI
View PDF12 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Embodiments of the present invention provide a method, device and storage medium for training classifiers based on sample features, which can solve the problem of low performance of classifiers in existing intrusion detection models

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method, device and storage medium for training classifier based on sample features
  • Method, device and storage medium for training classifier based on sample features
  • Method, device and storage medium for training classifier based on sample features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0060] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0061] An embodiment of the present invention provides a method for training a classifier based on sample features, such as figure 1 As shown, the method includes:

[0062] 101. Acquire a sample data set for training a classifier.

[0063] 102. Select N sample data in the sample data set as a target sample data set.

[0064] Wherein, N is a positive integer smaller than M, and M is the total number of sample data in the sample data set.

[0065] 103. Select...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The embodiment of the invention discloses a method, device and storage medium for training a classifier based on sample features, and relates to the field of network security. The method of the present invention includes: obtaining a sample data set for training a classifier; selecting N sample data in the sample data set as a target sample data set; wherein, N is a positive integer less than M, and M is the sample The total number of sample data in the data set; through information gain and correlation sorting, select the characteristics of each sample data in the target sample data set; perform feature weighted transformation on each of the sample features to obtain corresponding sample weighted features; based on each The sample weighted features are used to train the classifier. The invention can improve the classifier performance.

Description

technical field [0001] The present invention relates to the field of network security, in particular to a method, device and storage medium for training classifiers based on sample features. Background technique [0002] Most of the existing intrusion detection methods directly target all sample data and input them into classifiers for detection. However, in the actual network traffic data, due to the large scale of the data set, the performance of the classifier is reduced by using all the data sets to build the intrusion detection model. Contents of the invention [0003] Embodiments of the present invention provide a method, device and storage medium for training classifiers based on sample features, which can solve the problem of low performance of classifiers in existing intrusion detection models. [0004] In order to achieve the above object, embodiments of the present invention adopt the following technical solutions: [0005] In a first aspect, embodiments of th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06F21/55G06K9/62
CPCG06F21/552G06F18/24133
Inventor 魏金侠龙春赵静杨帆
Owner COMP NETWORK INFORMATION CENT CHINESE ACADEMY OF SCI