| 计算机网络自适应入侵检测模型研究 |
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| 引用本文： | 肖会敏.计算机网络自适应入侵检测模型研究[J].河南科学,2005,23(1):91-93. |
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| 作者姓名： | 肖会敏 |
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| 作者单位： | 河南财经学院计算机科学系,河南,郑州,450002 |
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| 基金项目： | 河南省自然科学基金资助课题(0311011500) |
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| 摘 要： | 传统的入侵检测系统(IDS)建立训练数据集时消耗的成本都非常高,自适应模型产生系统能够有效地解决这一问题,它可以为基于数据挖掘的入侵检测系统自动建立检测模型,而无需再用人工对数据做出标识。本文介绍了该模型的体系结构,并对其工作原理进行了分析,在此基础上建立自适应入侵检测模型。
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| 关 键 词： | 入侵检测系统 自适应 噪声数据 |
| 文章编号： | 1004-3918(2005)01-0091-03 |
| 修稿时间： | 2004年11月3日 |
Adaptive model for intrusion detection of computer network |
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| XIAO Hui-min.Adaptive model for intrusion detection of computer network[J].Henan Science,2005,23(1):91-93. |
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| Authors: | XIAO Hui-min |
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| Abstract: | The costs of constructing data sets to train misuse model and anomaly model are usually very expensive for conventional intrusion detection systems. The data mining-based adaptive model generation systems provides an effective solution to these, by automatically collecting data to train the detection models. In this paper, the architecture and the detection principle of adaptive model generation systems are studied, then the adaptive model for intrusion detection of computer network is established. |
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| Keywords: | intrusion detection system adaptive model noisy data |
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