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基于誤用和異常技術相結(jié)合的入侵檢測系統(tǒng)的設計與研究

田俊峰,  張喆,  趙衛(wèi)東

田俊峰, 張喆, 趙衛(wèi)東. 基于誤用和異常技術相結(jié)合的入侵檢測系統(tǒng)的設計與研究[J]. 電子與信息學報, 2006, 28(11): 2162-2166.
引用本文: 田俊峰, 張喆, 趙衛(wèi)東. 基于誤用和異常技術相結(jié)合的入侵檢測系統(tǒng)的設計與研究[J]. 電子與信息學報, 2006, 28(11): 2162-2166.
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.

基于誤用和異常技術相結(jié)合的入侵檢測系統(tǒng)的設計與研究

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

  • 摘要: 目前，入侵檢測系統(tǒng)(IDS) 的漏報率和誤報率高一直是困擾IDS用戶的主要問題，而入侵檢測系統(tǒng)主要有誤用型和異常型兩種檢測技術，根據(jù)這兩種檢測技術各自的優(yōu)點，以及它們的互補性，將兩種檢測技術結(jié)合起來的方案越來越多地應用于IDS中。該文提出了基于統(tǒng)計的異常檢測技術和基于模式匹配的誤用檢測技術相結(jié)合的IDS模型，減少了單純使用某種入侵檢測技術時的漏報率和誤報率，從而提高系統(tǒng)的安全性。
    Abstract: 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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  • 趙小林, 彭祖林, 王亞彬. 網(wǎng)絡安全技術教程. 北京: 國防工業(yè)出版社, 2002-1, 245－245.[2]蔣建春, 馬恒太, 任黨恩, 等. 網(wǎng)絡安全入侵檢測: 研究綜述. 軟件學報, 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]蔣建春, 馮登國. 網(wǎng)絡入侵檢測原理與技術. 北京: 國防工業(yè)出版社, 2001-7, 39－39.[6]李小秋, 孫學濤, 謝余強, 等. 入侵檢測系統(tǒng)中的快速多模式匹配算法. 計算機應用與軟件, 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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出版歷程
  • 收稿日期:  2005-03-08
  • 修回日期:  2005-09-26
  • 刊出日期:  2006-11-19

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