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	基于粗糙集的自适应入侵检测算法
	赵曦滨 ; 井然哲 ; 顾明 ; ZHAO Xibin ; JING Ranzhe ; GU Ming
	2010-05-12 ; 2010-05-12
关键词	粗糙集 计算机网络安全 知识约简 入侵检测 检测规则 rough sets computer network security attribute reduction intrusion detection detection rules TP393.08
其他题名	Adaptive intrusion detection algorithm based on rough sets
中文摘要	为了提高入侵检测系统的检测率,降低错检率,在分析现有入侵检测方法基础上提出一种基于粗糙集的入侵检测算法,将粗糙集算法和入侵检测技术结合起来实现系统的安全检测。对收集到的入侵数据进行预处理、数据离散化,属性约简,并依据生成的检测规则来分析入侵数据。实验结果表明:与基于BP(backpro pagation)神经网络和支持向量机的入侵检测算法比较,该算法的检测率提高10%左右,能很好地为信息系统提供入侵检测服务。; Intrusion detection systems are automatic system which recognize intrusions to computers or computer network systems.Existing security detection systems have many problems such as wrong detection of intrusions,missed intrusions,poor real-time performance.An intrusion detection algorithm was developed by combining a rough set algorithm with intrusion detection technology for security detection.The algorithm includes data preconditioning,data discretization,attribute reduction,production of detection rules,and finally analysis of intrusion data with these rules.Test results show that the intrusion detection algorithm is more efficient than algorithms based on BP neural networks and vector machines;thereby,improving the detection ratio by about 10% and reducing the wrong detection ratio.The system provides detection service effective for information systems.
语种	中文 ; 中文
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/28502]
专题	清华大学
推荐引用方式 GB/T 7714	赵曦滨,井然哲,顾明,等. 基于粗糙集的自适应入侵检测算法[J],2010, 2010.
APA	赵曦滨,井然哲,顾明,ZHAO Xibin,JING Ranzhe,&GU Ming.(2010).基于粗糙集的自适应入侵检测算法..
MLA	赵曦滨,et al."基于粗糙集的自适应入侵检测算法".(2010).

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