An active learning based TCM-KNN algorithm for supervised network intrusion detection

doi:10.1016/j.cose.2007.10.002

	An active learning based TCM-KNN algorithm for supervised network intrusion detection
	Li, Yang; Guo, Li
	2007-12-01
发表期刊	COMPUTERS & SECURITY
ISSN	0167-4048
卷号	26 期号:7-8 页码:459-467
摘要	As network attacks have increased in number and severity over the past few years, intrusion detection is increasingly becoming a critical component of secure information systems and supervised network intrusion detection has been an active and difficult research topic in the field of intrusion detection for many years. However, it hasn't been widely applied in practice due to some inherent issues. The most important reason is the difficulties in obtaining adequate attack data for the supervised classifiers to model the attack patterns, and the data acquisition task is always time-consuming and greatly relies on the domain experts. In this paper, we propose a novel supervised network intrusion detection method based on TCM-KNN (Transductive Confidence Machines for K-Nearest Neighbors) machine learning algorithm and active learning based training data selection method. It can effectively detect anomalies with high detection rate, low false positives under the circumstance of using much fewer selected data as well as selected features for training in comparison with the traditional supervised intrusion detection methods. A series of experimental results on the well-known KDD Cup 1999 data set demonstrate that the proposed method is more robust and effective than the state-of-the-art intrusion detection methods, as well as can be further optimized as discussed in this paper for real applications. (c) 2007 Elsevier Ltd. All rights reserved.
关键词	network security intrusion detection TCM-KNN (Transductive Confidence Machines for K-Nearest Neighbors) algorithm machine learning active learning
DOI	10.1016/j.cose.2007.10.002
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems
WOS记录号	WOS:000252611200003
出版者	ELSEVIER ADVANCED TECHNOLOGY
引用统计	被引频次：95[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/10967
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Yang
作者单位	Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Li, Yang,Guo, Li. An active learning based TCM-KNN algorithm for supervised network intrusion detection[J]. COMPUTERS & SECURITY,2007,26(7-8):459-467.
APA	Li, Yang,&Guo, Li.(2007).An active learning based TCM-KNN algorithm for supervised network intrusion detection.COMPUTERS & SECURITY,26(7-8),459-467.
MLA	Li, Yang,et al."An active learning based TCM-KNN algorithm for supervised network intrusion detection".COMPUTERS & SECURITY 26.7-8(2007):459-467.