| 基于数据挖掘的自适应入侵检测框架设计 |
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| 引用本文： | 刘永健,徐昕,王正华,薛倡新.基于数据挖掘的自适应入侵检测框架设计[J].计算机工程与应用,2006,42(14):152-154. |
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| 作者姓名： | 刘永健 徐昕 王正华 薛倡新 |
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| 作者单位： | 国防科学技术大学计算机学院,长沙,410073 |
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| 摘 要： | 数据挖掘、人工神经网络和机器学习等技术在入侵检测中的广泛应用,大幅度地提高了检测引擎的精度,但误用检测中的漏报率和异常检测中的误报率仍然是入侵检测中的难题。论文结合误用检测和异常检测的特点,利用机器学习思想,设计实现了一种新型的具有自适应能力的复合式入侵检测系统。
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| 关 键 词： | 复合引擎 自适应 数据清洗 数据挖掘 |
| 文章编号： | 1002-8331-（2006）14-0152-03 |
| 收稿时间： | 2005-09 |
| 修稿时间： | 2005-09 |
Design and Implementation of the Adaptive Intrusion Detection Framework Based on Data Mining |
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| Liu Yongjian,Xu Xin,Wang Zhenghua,Xue Changxin.Design and Implementation of the Adaptive Intrusion Detection Framework Based on Data Mining[J].Computer Engineering and Applications,2006,42(14):152-154. |
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| Authors: | Liu Yongjian Xu Xin Wang Zhenghua Xue Changxin |
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| Affiliation: | School of Computer Science,NUDT,Changsha 410073 |
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| Abstract: | The widely use of data mining,artificial neural network and machine learning in the intrusion detection has greatly improved the precision of the detection engine.However,the missed alarms in the misuse detection and the false alarms in the anomaly detection are still big problems.This paper combines the advantages of the misuse detection and the anomaly detection,integrates the idea of machine learning,designs and implements a novel compound intrusion detection system with self-adaptive ability. |
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| Keywords: | compound engine self-adaptive data cleaning data mining |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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