| 基于聚类的分类分析自适应入侵检测模型 |
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| 引用本文： | 廖明星.基于聚类的分类分析自适应入侵检测模型[J].数字社区&智能家居,2009,5(9):7101-7102. |
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| 作者姓名： | 廖明星 |
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| 作者单位： | 湖北大学,湖北武汉430062 |
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| 摘 要： | 基于数据挖掘的入侵检测系统由于引入了数据挖掘技术，很好的解决了传统入侵检测系统中自适应性和扩展性的问题。在数据挖掘中．聚类分析和分类分析是重要的技术，该文将这两种技术引入入侵检测模型，提出了一种基于聚类的分类分析自适应入侵检测模型。
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| 关 键 词： | 数据挖掘 入侵检测 分类 聚类 |
Adaptive Model of IDS with Classification Based on Clustering |
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| LIAO Ming-xing.Adaptive Model of IDS with Classification Based on Clustering[J].Digital Community & Smart Home,2009,5(9):7101-7102. |
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| Authors: | LIAO Ming-xing |
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| Affiliation: | LIAO Ming-xing (Hubei University, Wuhan 430062, China) |
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| Abstract: | Intrusion detection system based on data mining solves the problems about adaptability and extensibility in traditional intrusion detection system because of the data mining technology. Clustering and classification are important technologies in data mining. This paper introduces them in IDS and presents an adaptive model of IDS with classification based on clustering. |
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| Keywords: | data mining intrusion detection classification clustering |
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