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基于数据挖掘技术的入侵检测系统
引用本文:许盛中,蔡乐才,李红婵,姚行艳.基于数据挖掘技术的入侵检测系统[J].电子设计工程,2009,17(8).
作者姓名:许盛中  蔡乐才  李红婵  姚行艳
作者单位:1. 四川理工学院自动化与电子信息学院,四川,自贡,643000
2. 四川理工学院计算机科学系,四川,自贡,643000
摘    要:设计一个基于教据挖掘技术的入侵检测系统模型.该模型针对现有入侵检测系统在处理大量数据时,挖掘速度慢.自适应能力差的缺点.引入数据挖掘技术使其能从大量数据中发现入侵特征和模式.介绍其核心模块工作流程.实验结果表明该模型不仅能有效提高系统的检测速度,降低误报率,同时还能有效检测新的入侵行为.

关 键 词:入侵检测  自适应  数据挖掘  系统模型

Intrusion detection system based on data mining
XU Sheng-zhong,CAI Le-cai,LI Hong-chan,YAO Xing-yan.Intrusion detection system based on data mining[J].Electronic Design Engineering,2009,17(8).
Authors:XU Sheng-zhong  CAI Le-cai  LI Hong-chan  YAO Xing-yan
Abstract:The paper designs an intrusion detection system model based on data mining technology. Since the current intrusion detection system has weaknesses such as the lower speed in mining and the weakness in the self-adaptation ability,this paper constructs an intrusion detection system model based on the data mining technology.After introducing the technology,the intrusion detection system finds the intrusion characteristics and its pattern.The paper introduces its essential working part. The experimental results show that the model not only improves the detection speech of the system efficiently and cuts down the rate of false alarms,but also detects the new instruction behavior.
Keywords:intrusion detection  self-adaptation  data mining  system model
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