Research on Intrusion Detection Based on Improved Combination of K-means and Multi-level SVM

	Research on Intrusion Detection Based on Improved Combination of K-means and Multi-level SVM
	Zhang Xiaofeng 1; Hao Xiaohong 2
	2017
关键词	intrusion detection K-means SVM NSL-KDD
页码	2042-2045
英文摘要	Aiming at the problem that the traditional network intrusion detection algorithm has the advantages of low detection efficiency and high false alarm rate, a network intrusion detection algorithm based on improved K-means and multi-level SVM is proposed. The algorithm first divides the data to be detected into different clusters with the improved K-means, and marked as normal or abnormal; and then use the multi-level SVM to mark the abnormal cluster for detailed classification, the final realization of the detection of network attacks. The proposed intrusion detection algorithm uses the NSL-KDD data set to simulate the experiment. The results show that the proposed algorithm can improve the network intrusion detection rate and reduce the false alarm rate. It is an effective way of network security protection.
会议录	2017 17TH IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION TECHNOLOGY (ICCT 2017)
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
WOS研究方向	Engineering ; Telecommunications
WOS记录号	WOS:000435276600396
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36204]
专题	电气工程与信息工程学院
通讯作者	Zhang Xiaofeng
作者单位	1.Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China 2.Lanzhou Univ Technol, Sch Elect Engn & Informat Engn, Lanzhou 730050, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Zhang Xiaofeng,Hao Xiaohong. Research on Intrusion Detection Based on Improved Combination of K-means and Multi-level SVM[C]. 见:.