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Network exception detecting method based on artificial immunity principle

A technology of artificial immunity and network anomaly, applied in the field of network anomaly detection based on the principle of artificial immunity, can solve the problems of slow detection speed and low detection accuracy, and achieve the effect of fast detection speed, high detection accuracy and wide application prospects

Inactive Publication Date: 2009-07-08
GUANGDONG OCEAN UNIVERSITY
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AI Technical Summary

Problems solved by technology

This method has the nonlinearity of the biological immune system, as well as the excellent characteristics of clone selection, immune network and immune memory, and solves the problems of slow detection speed and low detection accuracy in the current network anomaly detection

Method used

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  • Network exception detecting method based on artificial immunity principle
  • Network exception detecting method based on artificial immunity principle
  • Network exception detecting method based on artificial immunity principle

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Embodiment Construction

[0048] Before explaining in detail, some nouns, symbols and some formulas used in the invention are first defined:

[0049] (1) Define M to represent a set of memory cells, m to represent a memory cell, and m∈M. Define B as an artificial antibody set, b represents an antibody cell and b ∈ B; define G as an antigen set, g represents an antigen, and g ∈ G; define C as an antigen set, and c represent a memory cell, antibody or antigen category, And c ∈ C.

[0050] (2) Define memory cell m, antibody cell b, antigen g consists of categories and feature vectors, namely , where m.c represents the category of memory cells mc, and m.c∈C={0, 1}, b.c and g.c represent antibody and antigen categories respectively, and b.c∈C={0, 1}, g.c∈C={0, 1}, where 0 indicates normal network behavior and 1 indicates abnormal network behavior. g.f, m.f, and b.f represent the eigenvectors of g, m, and b respectively, and the eigenvectors are composed of characteristic data describing network transactio...

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Abstract

The invention provides a network anomaly detection method based on an artificial immunity principle belonging to information safety field. The invention implements the network anomaly detection method capable of fast detecting with high detection accuracy by simulating biological immune system response to external antigen, training antigen data collection and artificial immune system study, and detecting network anomaly. The network anomaly detection method has superior characteristics of a non-linearity of the biological immune system, cloning selection, immune network and immunological memory, solves the problems of low detection speed and low detection accuracy in the present network anomaly detection. The invention also applies to the pattern recognition, machine learning fields and has wide application prospect.

Description

technical field [0001] The invention belongs to a network anomaly detection method based on the principle of artificial immunity. Background technique [0002] With the continuous development of the Internet, network security has gradually become a problem that people are more and more concerned about, and intrusion detection technology is one of the detection methods that have gradually emerged after the firewall, and it has also attracted more and more attention from scholars and engineers. Traditional intrusion detection methods are divided into two types: misuse detection methods and anomaly detection methods. Among them, misuse detection forms attack signature data for known attacks. Unless the attack signature database is updated to the latest, related attacks cannot be detected; while anomaly detection methods model normal user behavior and protected systems. When new data deviates from the normal model, it is considered abnormal. Since the anomaly detection method ...

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Application Information

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IPC IPC(8): H04L29/06H04L12/24G06N3/00
Inventor 彭凌西沈玉利范锐张健刘双印陈月峰徐龙琴朱旭东梁春林
Owner GUANGDONG OCEAN UNIVERSITY
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