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基于数据挖掘的网络入侵检测研究 被引量:5

Research on Intrusion Detection based on Data Mining
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摘要 探讨了数据挖掘技术应用于网络入侵检测的可行性和必要性,提出一种基于数据挖掘的入侵检测模型,并对该模型中K-means算法进行研究。该检测模型的建立不依赖于经验数据,能自动对网络行为数据进行入侵检测。仿真实验表明,该方法能极大地提高检测效率和准度,具有较强的实用性和自适应性。 This paper discusses the feasibility and necessity of data mining techniques applied to network intrusion detection, introduces an intrusion detection model based on data mining. Build a model of the detector data does not depend on the experience, network behavior data can be automatically carried out on the network intrusion detection. Simulation results show that the method has a strong practical and adaptability to improve the detection efficiency and accuracy.
出处 《计算机安全》 2014年第7期14-17,共4页 Network & Computer Security
基金 湖北省教育厅人文社科项目(13q088) 湖北汽车工业学院博士基金项目(BK201203)
关键词 数据挖掘 入侵检测 聚类算法 K-MEANS算法 网络安全 data mining intrusion detection clustering algorithm K-means algorithm network security
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