期刊文献+

一种新型的无线网络入侵检测方法-动态自适应模板法

A New Intrusion-detection Method In Wireless Network Dynamic Self-Adaptation Model Method
原文传递
导出
摘要 为了能够检测到无线网络系统中的已知和未知类型的入侵者,提高无线网络系统的安全性,本文提出了动态自适应模板法。该方法的基本思想是原有模板(分类结果)在聚类过程中不断更新,并且允许在聚类分析过程中构成新的模板。实验表明用该方法检测无线网络系统中的新型入侵者,准确率可达到98%。 In order to improve the detection rate of new intruders in wireless network intrusion detection system(IDS),The dynamic self-adaptation model method is developed in this paper.The basic thought of the method is that original model is updated continuously,and the new model can formed in cluster.Experimental results show that this method is useful and applicable,and the detection right rate of new intruders in Wireless Network can get to 98%.
出处 《网络安全技术与应用》 2011年第9期35-37,77,共4页 Network Security Technology & Application
基金 北京建筑工程学院科学研究基金项目(批准号:100803807)资助
关键词 检测新型入侵者 无线网络 动态自适应模板 Detecting new intrusion Wireless Networks Dynamic self-adaptation model
  • 相关文献

参考文献4

  • 1卿斯汉,蒋建春,马恒太,文伟平,刘雪飞.入侵检测技术研究综述[J].通信学报,2004,25(7):19-29. 被引量:234
  • 2YG.Zhang.lntrusion Detection Techniques for Mobile Wireless Networks[J].Wireless Networks.2003.
  • 3YG.Zhang.Feature Deduction and Ensemble design of Intrusion Systems[J].Computers & Security.2004.
  • 4WK.LEE.Feature Selection of Intrusion Data using a hybrid genetic algorithm Approach[J].Wireless Networks.2007.

二级参考文献46

  • 1LEE W,STOLFO S,MOK K. A data mining framework for adaptive intrusion detection[EB/OL]. http://www.cs.columbia.edu/~sal/ hpapers/framework.ps.gz.
  • 2LEE W, STOLFO S J, MOK K. Algorithms for mining system audit data[EB/OL]. http://citeseer.ist.psu.edu/lee99algorithms.html. 1999.
  • 3KRUEGEL C, TOTH T, KIRDA E.Service specific anomaly detection for network intrusion detection[A]. Proceedings of the 2002 ACM Symposium on Applied Computing[C]. Madrid, Spain, 2002. 201-208.
  • 4LIAO Y, VEMURI V R. Use of text categorization techniques for intrusion detection[A]. 11th USENIX Security Symposium[C]. San Francisco, CA, 2002.
  • 5An extensible stateful intrusion detection system[EB/OL]. http://www.cs.ucsb.edu/~kemm/NetSTAT/doc/index.html.
  • 6ILGUN K. USTAT: A Real-Time Intrusion Detection System for UNIX[D]. Computer Science Dep University of California Santa Barbara, 1992.
  • 7The open source network intrusion detection system [EB/OL]. http://www.snort.org/.
  • 8KO C, FINK G, LEVITT K. Automated detection of vulnerabilities in privileged programs by execution monitoring[A]. Proceedings of the 10th Annual Computer Security Applications Conference [C]. Orlando, FL: IEEE Computer Society Press, 1994. 134-144.
  • 9Computer security & other applications of immunology[EB/OL]. http://www.cs.unm.edu/~forrest/isa_papers.htm.
  • 10GRUNDSCHOBER S. Sniffer Detector Report[R]. IBM Research Division Zurich Research Laboratory Global Security Analysis Lab, 1998.

共引文献233

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部