Genetic Algorithms in Intrusion Detection Based on Network Anomaly

ZHANG Feng-bin; YANG Yong-tian; JIANG Zi-yang

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Genetic Algorithms in Intrusion Detection Based on Network Anomaly

更新时间：2025-07-16

- Genetic Algorithms in Intrusion Detection Based on Network Anomaly
- Acta Electronica Sinica Vol. 32, Issue 5, Pages: 875-877(2004)
- 作者机构：
  
  1. 哈尔滨工程大学计算机科学与技术学院,黑龙江,哈尔滨,150001
  2. 哈尔滨理工大学计算机与控制学院,黑龙江,哈尔滨,150080
  3. 哈尔滨工程大学计算机科学与技术学院黑龙江哈尔滨,150001
  4. 哈尔滨理工大学计算机与控制学院黑龙江哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.08
- Published：2004
- 稿件说明：
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ZHANG Feng-bin, YANG Yong-tian, JIANG Zi-yang. Genetic Algorithms in Intrusion Detection Based on Network Anomaly[J]. Acta Electronica Sinica, 2004, 32(5): 875-877.
DOI：

ZHANG Feng-bin, YANG Yong-tian, JIANG Zi-yang. Genetic Algorithms in Intrusion Detection Based on Network Anomaly[J]. Acta Electronica Sinica, 2004, 32(5): 875-877. DOI：

摘要

考虑到基于误用的IDS不能有效检测未知入侵行为

而基于统计的异常检测法在建模时忽略了多变量在一段时间内的关系

提出了一种异常检测算法.用滑动窗口将系统各属性表示为特征向量

从而将系统正常状态分布在

维空间中

并使用遗传算法进化检测规则集来覆盖异常空间.经实验证明该方法提高了检测率.

Abstract

Intrusion detection system(IDS) based on misuse couldn't detect undefined intrusion behavior effectively and anomaly detection methods based on statistic ignored multivariable correlations of variables in amount of time.A novel anomaly detection algorithm was proposed.Feature vectors represent the system's attributes with slide window and distribute the normal system sate in n dimension space in this method.The method use rules set evolved with genetic algorithms to cover the abnormal space.Experiment shows that the algorithm improves the detection rate.

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