Distributed intrusion detection system based on ARTIS

被引：2

作者：

Qiao, PL ^{[1
]}

Su, J ^{[1
]}

Sun, CW ^{[1
]}

机构：

[1] Harbin Univ Sci & Technol, Harbin 150080, Peoples R China

来源：

Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005 | 2005年 / 5812卷

关键词：

Intrusion Detection System (IDS); Artificial Immune System (ARTIS); immune algorithm; immune memory; NIDS;

D O I：

10.1117/12.601862

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Traditional IDS (Intrusion Detection System) performs detection by matching the sample pattern with the intrusion pattern that has been defined, as a result the IDS loses the diversity and the self-adaptation and can not detect the variation intrusion and the unknown intrusion. This paper gives a distributed intrusion detection approach based on the Artificial Immune System. It defines the Self, Nonself and immune cell and builds an intrusion detection model composed of memory cell, mature cell and immature cell and also gives the environment definition, matching rule, training detection system, immune regulation and memory, monitor generation and so on. The result of the experiment show that this intrusion detection system model has the characters of distributed, error tolerance, dynamic learning, adaptation and this approach is efficient to the network intrusion detection.

引用

页码：356 / 363

页数：8