Network anomaly detection based on TCM-KNN and genetic algorithm

LI Yang1; FANG Bin-xing1; GUO Li1; TIAN Zhi-hong1; ZHANG Yong-zheng1; JIANG Wei1

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Network anomaly detection based on TCM-KNN and genetic algorithm

更新时间：2024-10-14

- Network anomaly detection based on TCM-KNN and genetic algorithm
- Issue 12, Pages: 48-52(2007)
- 作者机构：
  
  1. 中国科学院计算技术研究所
  2. 中国科学院计算技术研究所,北京,100080
  3. 中国科学院研究生院
  4. ,北京,100039
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18;TP393.08
- Published：2007
- 稿件说明：
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LI Yang1, FANG Bin-xing1, GUO Li1, et al. Network anomaly detection based on TCM-KNN and genetic algorithm[J]. 2007, (12): 48-52.
DOI：

LI Yang1, FANG Bin-xing1, GUO Li1, et al. Network anomaly detection based on TCM-KNN and genetic algorithm[J]. 2007, (12): 48-52. DOI：

摘要

提出了一种基于TCM-KNN的网络异常检测新方法

并采用遗传算法选择使用少量高质量的训练样本进行建模

从而有效地对入侵进行检测。大量基于著名的KDD Cup 1999数据集的实验表明:其相对于传统的异常检测方法在保证较高检测率的前提下

有效地降低了误报率;并且

在采用选择后的训练集优化处理后

其性能没有明显的削减

因而相对于传统方法更为适用于现实的网络应用环境。

Abstract

A network anomaly detection scheme based on TCM-KNN algorithm was proposed.Moreover

genetic algo-rithm（GA） based instance selection was introduced to boost the detection performance

meanwhile reduce the computa-tional cost for TCM-KNN.A series of experimental results demonstrate the proposed method is effective

the instance se-lection mechanism also improves TCM-KNN and makes it be a good candidate for anomaly detection in practice.

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Related Author

LI Yang1

GUO Li1

LU Tian-bo3

TIAN Zhi-hong1

YANG Wu1

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ZHOU Yuan2

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Related Institution

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