An active learning based TCM-KNN algorithm for supervised network intrusion detection
文献类型：期刊论文
| 作者 | Li, Yang; Guo, Li |
| 刊名 | COMPUTERS & SECURITY
 |
| 出版日期 | 2007-12-01 |
| 卷号 | 26期号:7-8页码:459-467 |
| 关键词 | network security intrusion detection TCM-KNN (Transductive Confidence Machines for K-Nearest Neighbors) algorithm machine learning active learning |
| ISSN号 | 0167-4048 |
| DOI | 10.1016/j.cose.2007.10.002 |
| 英文摘要 | 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. |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000252611200003 |
| 出版者 | ELSEVIER ADVANCED TECHNOLOGY |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/10966]  |
| 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. |
入库方式： OAI收割
来源：计算技术研究所
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