期刊文献+

小型网络入侵检测系统研究

Research of Small Network Intrusion Detection System
下载PDF
导出
摘要 提出了一个适用于小型网络的入侵检测系统框架,由包捕获器,包解码器,事件检测器和事件处理器构成,能对网络流量进行实时监控。特别在事件检测器中,针对采集的数据包头和数据包内容这两部分进行综合分析,采用规则检测技术进行异常行为检测,能更精确地检测入侵行为。通过实验证明了系统的检出率有明显提高,同时降低了误报率。 This paper gives a kind of frame of intrusion detection system suitable for small network.It consists of package capturer,package decoder,event detector and event processor.It inspects the network dataflow on real time,and especially establishes event detector based on rule detection.It gives the focus on the analysis on header and content of network packet,and the system can increase detection rate of intrusion action.It is proved that the system improves the detection rate and accuracy proved by experiments.
出处 《咸阳师范学院学报》 2010年第6期40-42,52,共4页 Journal of Xianyang Normal University
基金 陕西省教育厅科研基金项目(08JK481) 咸阳师范学院科研基金项目(06XSYK282)
关键词 网络安全 入侵检测 规则检测 network security intrusion detection rule detection
  • 相关文献

参考文献5

  • 1段友祥,孙冰,王海峰.基于Lisys的人工免疫入侵检测模型研究[J].微计算机应用,2007,28(4):363-367. 被引量:1
  • 2Yang Rong,Leung WS,Heng P A,et al.Improved algorithm on rRule-based reasoning systems modeled by fuzzy petri nets[C].Proceedings of the IEEE International Conference on Fuxxy Systems,2002-5-12,2:1204-1209.
  • 3Norton M,Roelker D.Hi-performance multi-rule inspection engine[Z].http://www.snortorg,2004-04.
  • 4Dasgupta D,Gonzalz F.An immunity-based technique to characterize intrusions in computer networks[J].IEEE Transactions on Evolutionary Computation,2002,6(3):281-291.
  • 5Coit J C,Staniford S,Mcalemey J.Towards faster string matching for iIntrusion detection[C].Proc of DARPA Information Survivability Conference and Exposition,2001:367-373.

二级参考文献5

  • 1D. Dasgupta, Artificial immune system and their application. Springer- Verlag, 1998.
  • 2J. Balthrop, S. Forrest and M. Glickman. Revisiting lisys: Parameters and normal behavior. In CEC -2002: Proceedings of the Congress on Evolutionary Computing, 2002.
  • 3S. Hofmeyr and S. Forrest. Architecture for an artificial immune system. Evolutionary Computation Journal,2000, 8(4) :443 -473
  • 4D. Daagupta,S. Yu, N. Majumdar. MILA Multi -level immune learning algorithm. Genetic and Evolutionary Computation Conference (GECCO'2003), 2003,183 - 194, Chicago, USA, July 12 -6
  • 5D. Dasgupta, N. Majumdar, S. Yu. Multi-level immune learning algorithm: Preliminary results. Technical report CS-02-003, May 2002.

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