| 入侵检测的可进化模糊规则分类器研究 |
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| 引用本文： | 周豫苹,方建安,于冬梅. 入侵检测的可进化模糊规则分类器研究[J]. 计算机工程与科学, 2009, 31(8) |
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| 作者姓名： | 周豫苹 方建安 于冬梅 |
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| 作者单位： | 1. 东华大学信息科学与技术学院,上海,201620;漳州师范学院计算机科学与工程系,福建,漳州,363000
2. 东华大学信息科学与技术学院,上海,201620 |
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| 基金项目： | 国家自然科学基金，福建省教育厅科技基金 |
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| 摘 要： | 随着入侵检测技术(IDS)在网络安全领域的作用越来越重要,将多种软计算方法应用到入侵检测技术中是构建智能入侵检测系统的新途径和尝试。本文将模糊数据挖掘技术和遗传算法相结合,提出一种基于遗传算法的模糊规则反复学习的方法,构造具有自适应能力的分类器,并进一步应用到计算机网络的入侵检测中。仿真测试证明了该方法的有效性。
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| 关 键 词： | 入侵检测 模糊逻辑 遗传算法 分类器 |
A Study of the Evolving Fuzzy Rule-Based Classifier in Intrusion Detection |
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| ZHOU Yu-ping,FANG Jian-an,YU Dong-mei. A Study of the Evolving Fuzzy Rule-Based Classifier in Intrusion Detection[J]. Computer Engineering & Science, 2009, 31(8) |
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| Authors: | ZHOU Yu-ping FANG Jian-an YU Dong-mei |
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| Abstract: | Intrusion detection techniques become increasingly important in the area of network security. It is a novel attempt that various soft computing approaches are applied to the intrusion detection field. This paper combines the fuzzy data mining technology and genetic algorithms,describes a fuzzy genetic-based learning algorithm,constructs a fuzzy rule classifier and discusses its usage to further detect intrusion in a computer network. Experimental results indicate the efficiency of the algorithm. |
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| Keywords: | intrusion detection fuzzy logic genetic algorithm classifier |
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