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基于SVM技术的入侵检测 被引量:11

AN INTRUSION DETECTION METHOD BASED ON SVM
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摘要 针对日益严重的网络入侵事件 ,提出了一种新的入侵检测方法 .在对网络数据进行深刻的分析和研究的基础上 ,提出了基于支持向量机的入侵检测方法 .首先 ,对 1类SVM进行了必要的改进 ,使异常点聚集为一类 (即环绕原点的一类 ) .然后 ,使用抽象化的网络数据对SVM进行训练 ,生成入侵事件的SVM分类器 .实验表明 。 For the growing web intrusion issues, We propose a new method for intrusion detection. In this paper, we first make deep analysis on the attacks and misuse patterns in log files; and then propose a method with support vector machines for anomaly detection. The one-class SVM for our intrusion detection task is improved, so as to make the novelty data cluster in one class (the negative class around the origin). And the SVM classifier is generated and trained with abstracted data. Experimental results show that this method is effecfive.
出处 《信息与控制》 CSCD 北大核心 2003年第6期495-499,506,共6页 Information and Control
基金 国家"十五"科技攻关计划重点资助项目 ( 2 0 0 2BA40 7B) 河北省自然科学基金资助项目 ( 60 3 13 7)
关键词 入侵检测 网络安全体系 SVM技术 支持向量机 计算机网络 网络数据 information security intrusion detection anomaly detection misuse detection one-class SVM
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参考文献9

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