期刊文献+

危险模式入侵检测报警算法优化 被引量:1

Optimization Algorithm of Alarm for Intrusion-detection System
下载PDF
导出
摘要 由于高流量的网络环境中危险区域难以确定,提出报警信息的分析方案,从报警信息挖掘频繁闭序列。频繁闭项集的数量远小于频繁项集,而且通过频繁闭项集能得到所有的频繁项集,对报警消息频繁闭项集进行关联分析,可以将大量的报警消息相互关联起来,有效地缩减报警数量,提高危险模式入侵检测与响应系统的效率。 In view of the hard detection of hazardous locations in the network traffic,an analysis on the alarm messages from which the frequent close-up sequences can be excavated in the network environment,is proposed in this paper.As the number of the close-up frequent itemsets is far less than that of the frequent itemsets which can be obtained via the close-up frequent itemsets,a large number of alarm messages can be correlated by a correlation analysis on the frequent close-up sequences of the alarm messages.In this way,not only can the times of warning be reduced,but the efficiency of the system of the intrusion-detection and the response can be improved.
作者 王慧
出处 《煤炭技术》 CAS 北大核心 2010年第10期175-176,179,共3页 Coal Technology
关键词 入侵检测 危险模式 频繁模式 关联规则 intrusion-detection system danger model frequent pattern correlation rules
  • 相关文献

参考文献2

二级参考文献1

  • 1王峰波,计算机工程与科学,2000年,22卷,2期,62页

共引文献45

同被引文献10

  • 1Biswanath Mukherj ee,Todd L Heberlein, Karl NLevitt. Network intrusion detection [J]. IEEE Net-work, 1994,8(3):26-41.
  • 2W Lee, S J Stolfo. Data mining approaches for intrusiondetection[C]//Proceedings of the 7th USENIX Secur-ity Symposium,Oakland,California : IEEE ,1998.
  • 3Fox K L,Henning R R,Reed J H,et al. A neural net-work approach toward intrusion detection[C]//Pro-ceeding Of the 10th National Computer Security Con-ferene. [s. 1.]. IEEE, 1990: 116-174.
  • 4L R Rabiner and B H Juang. An introduction to hiddenMarkov models [J], IEEE ASSP Magazine, 1986: 4- 16.
  • 5Matzinger P. Tolerance,danger,and the extended fami-ly[J]. Ann Rev Immunol, 1994(12) : 991-1046.
  • 6Matzinger P. Essay lathe danger model in its historicalcontext[J]. Scand J Immunol,2001(4) :4-9.
  • 7Yingfeng Chen,Lianying Zhou. An innovative IDS im-mune system model proceedings of the internationalconference on systems uan and cybernetics. Hague:IEEE, 2004 :4810-4814.
  • 8Xuo-Yuan Yang, Wan-Wu ZHou, PingWei. HybridNIDS based on biological immunology[C] // Proceed-ings of 2004 International Coxference on Uachine Lea-ring and Cybernetics, [s. 1.] : IEEE, 2004 : 2889-2892.
  • 9许国艳,史宇清.遗传算法在关联规则挖掘中的应用[J].计算机工程,2002,28(7):122-124. 被引量:28
  • 10贾兆红,倪志伟,赵鹏.改进型遗传算法及其在数据挖掘中的应用[J].计算机应用,2002,22(9):31-33. 被引量:23

引证文献1

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