Improving of Detector in Intrusion Detection Model Based on Immuno-genetic Algorithms(IGA)

QIAO Pei-li; YUAN Shuo

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Improving of Detector in Intrusion Detection Model Based on Immuno-genetic Algorithms(IGA)

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- Improving of Detector in Intrusion Detection Model Based on Immuno-genetic Algorithms(IGA)
- Vol. 16, Issue 3, Pages: 35-40(2011)
- 作者机构：
  
  哈尔滨理工大学计算机科学与技术学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP393.08
- Published：2011
- 稿件说明：
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QIAO Pei-li, YUAN Shuo. Improving of Detector in Intrusion Detection Model Based on Immuno-genetic Algorithms(IGA)[J]. 2011, 16(3): 35-40.
DOI：

QIAO Pei-li, YUAN Shuo. Improving of Detector in Intrusion Detection Model Based on Immuno-genetic Algorithms(IGA)[J]. 2011, 16(3): 35-40. DOI：

摘要

针对检测器算法收敛速度慢并且容易陷入早熟的缺点

依据传统的GA理论模型

引入了检测器冗余优化概念

利用均匀设计抽样理论

给出了一种检测器优化方案.对遗传算法中的交叉遗传算子进行了重新设计

对染色体的相似度及其相关内容进行了改进并使之与检测器冗余建立关联

得到了局部搜索策略和一种冗余数求解新方法.仿真实验表明

此改进方案保持了检测器的多样性、高效性以及其适应度水平

从而使检测器在搜索速度、全局寻优、提高检测率并降低误报率方面的性能得到明显改善.

Abstract

The purpose of this paper is to give a new detector prioritization scheme which is founded on the basis of the combination of partial searching strategy and a new method to evaluate the data of redundancy.Based on traditional theoretical model of GA

the Optimization of Detector Redundancy

a new concept

with relevant content is introduced in this paper.Aiming at the low velocity algorithm convergence and its shortcomings of easy early-maturing

the theory of Uniform Design Sampling(UDS) are used to redesign t...

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