A lightweight web server anomaly detection method based on transductive scheme and genetic algorithms
文献类型：期刊论文
| 作者 | Li, Yang1,2; Guo, Li2; Tian, Zhi-Hong2; Lu, Tian-Bo3 |
| 刊名 | COMPUTER COMMUNICATIONS
 |
| 出版日期 | 2008-11-20 |
| 卷号 | 31期号:17页码:4018-4025 |
| 关键词 | Network security Web server anomaly detection TCM-KNN algorithm Genetic algorithm |
| ISSN号 | 0140-3664 |
| DOI | 10.1016/j.comcom.2008.08.009 |
| 英文摘要 | World Wide Web (WWW) is one of the most popular applications currently running on the Internet and web server is a crucial component for this application. However, network anomalies especially Distributed Denial-of-Service (DDoS) attacks bombard web server, degrade its Quality of Service (QoS) and even deny the legitimate users' requests. Traditional network anomaly detection methods often lead to high false positives and expensive computational cost, thus unqualified for real-time web server anomaly detection. To solve these problems, in this paper we first propose an efficient network anomaly detection method based on Transductive Confidence Machines for K-Nearest Neighbors (TCM-KNN) algorithm. Secondly, we integrate a lot of objective and efficient anomalies impact metrics from the perceptions of the end users into TCM-KNN algorithm to build a robust web sever anomaly detection mechanism. Finally, Genetic Algorithm (GA) based instance selection method is introduced to boost the real-time detection performance of our method. We evaluate our method on a series of experiments both on well-known KDD Cup 1999 dataset and concrete dataset collected from real network traffic. The results demonstrate our methods are actually effective and lightweight for real-time web server anomaly detection. (C) 2008 Elsevier B.V. All rights reserved. |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000261362400014 |
| 出版者 | ELSEVIER SCIENCE BV |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/11357]  |
| 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 | 1.China Mobile Res Inst, Beijing 100053, Peoples R China 2.Chinese Acad Sci, Comp Technol Inst, Beijing 100190, Peoples R China 3.Natl Comp Network Emergency Response Tech Team Co, Beijing 100029, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Yang,Guo, Li,Tian, Zhi-Hong,et al. A lightweight web server anomaly detection method based on transductive scheme and genetic algorithms[J]. COMPUTER COMMUNICATIONS,2008,31(17):4018-4025. |
| APA | Li, Yang,Guo, Li,Tian, Zhi-Hong,&Lu, Tian-Bo.(2008).A lightweight web server anomaly detection method based on transductive scheme and genetic algorithms.COMPUTER COMMUNICATIONS,31(17),4018-4025. |
| MLA | Li, Yang,et al."A lightweight web server anomaly detection method based on transductive scheme and genetic algorithms".COMPUTER COMMUNICATIONS 31.17(2008):4018-4025. |
入库方式： OAI收割
来源：计算技术研究所
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