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Volume 28 Issue 11
Sep.  2010
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Tian Jun-feng, Zhang Zhe, Zhao Wei-dong. The Design and Research of Intrusion Detection System Based on Misuse and Anomaly[J]. Journal of Electronics & Information Technology, 2006, 28(11): 2162-2166.
Citation: Tian Jun-feng, Zhang Zhe, Zhao Wei-dong. The Design and Research of Intrusion Detection System Based on Misuse and Anomaly[J]. Journal of Electronics & Information Technology, 2006, 28(11): 2162-2166.

The Design and Research of Intrusion Detection System Based on Misuse and Anomaly

  • Received Date: 2005-03-08
  • Rev Recd Date: 2005-09-26
  • Publish Date: 2006-11-19
  • Currently, the false positive and the false negative of Intrusion Detection System are very high. It was always the main problem that bothered the user of IDS. But there are tow main technologies applied in IDS. To this problem, because both the technologies have its own advantages and they can supply for each other. So IDS combined with the tow technologies was used more and more widely. This paper presented a model of IDS based on combination of misuse detection and anomaly detection. In this model, misuse detection is based on pattern matching and Anomaly Detection is based on statistical analysis. It combined the tow technologies to reduce the false positive rate and the false negative rate in only one detection technology, and then to improve security of IDS.
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  • 赵小林, 彭祖林, 王亚彬. 网络安全技术教程. 北京: 国防工业出版社, 2002-1, 245-245.[2]蒋建春, 马恒太, 任党恩, 等. 网络安全入侵检测: 研究综述. 软件学报, 2000, 11(11): 1460-1466.[3]Fumio Mizoguchi. Anomaly Detection Using Visualization and Machine Learning. IEEE 9th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises. Gaithersburg, Maryland: March 14-16, 2000: 165-170.[4]Shan Zheng, Chen Peng, Xu Ke, et al.. A Network State Based Intrusion Detection Model. 2001 International Conference on Computer Networks and Mobile Computing. Beijing, CHINA: October 16 -19, 2001: 481-486.[5]蒋建春, 冯登国. 网络入侵检测原理与技术. 北京: 国防工业出版社, 2001-7, 39-39.[6]李小秋, 孙学涛, 谢余强, 等. 入侵检测系统中的快速多模式匹配算法. 计算机应用与软件, 2004-02, 21(2): 84-86.[7]Koral Ilgun, Richard A.Kemmerer, Phillip A.Porras. State transition analysis: A rule-based intrusion detection approach. IEEE Trans. on Software Engineering, 1995-3, 21(3): 181-199.[8]Nittida Nuansri, Samar Singh, Tharam S.Dillon. A Process State-Transition Analysis and its Application to Intrusion Detection. 15th Annual Computer Security Applications Conference. Phoenix, Arizona:December 06-10, 1999: 378-387.[9]Nong Ye, Syed Masum Emran, Xiangyang Li, et al.. Statistical Process Control for Computer Intrusion Detection[J].DARPA Information Survivability Conference Exposition Anaheim, California: June 12-1.2001, 1(1):3-
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