| 基于遗传优化与模糊规则挖掘的异常入侵检测 |
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| 引用本文： | 徐东升,艾晓燕,阎世梁.基于遗传优化与模糊规则挖掘的异常入侵检测[J].计算机应用,2009,29(8). |
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| 作者姓名： | 徐东升 艾晓燕 阎世梁 |
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| 作者单位： | 1. 榆林学院,信息技术系,陕西,榆林,719000
2. 西南科技大学,工程技术中心,四川,绵阳,621010 |
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| 基金项目： | 陕西省榆林市科技计划项目 |
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| 摘 要： | 提出一种基于智能体进化计算框架与遗传模糊规则挖掘的异常入侵检测方法.通过应用模糊集分布策略、解释性的控制策略和模糊规则生成策略,实现了Agent之间的模糊集信息交换,从而有效地从网络数据中抽取正确的、可解释的模糊IF-THEN分类规则,优化了模糊系统的可解释性,并提高了系统的紧凑性.采用KDD-Cup99数据集进行测试,并与现有方法进行了比较,结果表明该方法对R2L的攻击检测性能稍弱,对DoS、Probe和U2R的攻击均具有较高的分类精度与较低的误报率.
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| 关 键 词： | 遗传模糊系统 多目标优化 遗传算法 规则提取 入侵检测 |
Anomaly intrusion detection based on genetic optimization and fuzzy rules mining |
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| XU Dong-sheng,AI Xiao-yan,YAN Shi-liang.Anomaly intrusion detection based on genetic optimization and fuzzy rules mining[J].journal of Computer Applications,2009,29(8). |
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| Authors: | XU Dong-sheng AI Xiao-yan YAN Shi-liang |
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| Affiliation: | 1. Department of Information Technology;Yulin University;Yulin Shaanxi 719000;China;2. Engineering and Technology Center;Southwest University of Science and Technology;Mianyang Sichuan 621010;China |
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| Abstract: | A genetic-fuzzy rule mining approach applied to anomaly intrusion detection was proposed, with an Agent-based evolutionary computing framework. Due to the exchanging of fuzzy sets information among the fuzzy sets Agents, accurate and interpretable fuzzy IF-THEN rules could be extracted from network traffic data for optimizing the interpretability and improving the compactivity of the fuzzy systems, by using three strategies including fuzzy sets distribution, interpretable regulation and fuzzy rules generati... |
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| Keywords: | genetic-fuzzy system multi-objective optimization genetic algorithm rule extraction intrusion detection |
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