期刊文献+

一种基于聚类和协议分析的入侵检测方法 被引量:1

Intrusion detection method based on clustering and protocol analysis
下载PDF
导出
摘要 根据入侵检测中协议分析技术与聚类数据挖掘技术各自不同的检测特点,提出了一种新的入侵检测方法,将协议分析技术融合到聚类数据挖掘中。通过数据清洗和协议分析不但可以有效减少聚类挖掘的数据量,快速地检测出入侵行为,而且可以让被挖掘的数据更加符合聚类数据挖掘的先决条件,提高了聚类数据挖掘检测的效率。 Because of the altitudinal regularity of the network protocol of the data package,a new intrusion detection method is suggested,in order to improve the efficiency.The protocol analysis technique is suggested to be attached to the clustering data mining method.On the one hand,it can take out the illegal data efficiently by reducing the amount of data set which is to be clustered,on the other hand,it can make the data set measure up the hypothesis of the clustering data mining technique,and make the work more efficient.
出处 《计算机工程与应用》 CSCD 北大核心 2009年第14期81-83,共3页 Computer Engineering and Applications
基金 国家自然科学基金No.60773083 广东省科技计划项目(No.2006B15401002)~~
关键词 入侵检测 数据挖掘 聚类 协议分析 intrusion detection data mining clustering protocol analysis
  • 相关文献

参考文献5

二级参考文献14

  • 1Eskin E. Anomaly detection over noisy data using learned probability distributions[C]. In: Proceedings of the Seventeenth International Conference on Machine Learning (ICML-2000),2000,June 29-July 02,255-262.
  • 2Portnoy L, Eskin E, Stolfo S J. Intrusion detection with unlabeled data using clustering[C]. In: Proceedings of ACM CSS Workshop on Data Mining Applied to Security (DMSA-2001).Philadelphia, PA: November 5-8, 2001.
  • 3Eskin E, Arnold A, Prerau M et al. A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data[A]. In:Data Mining for Security Applications[M],Kluwer, 2002.
  • 4Lee W K, Stolfo S J, Mok K W. Mining in a data-flow environment: experience in network intrusion detection[C]. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-99), August 1999.
  • 5Li Xiang-yang. Clustering and classification algorithm for computer intrusion detection[D]. Arizona State University,2001.
  • 6Charles Elkan. Results of the KDD'99 classifier learning contest[EB/OL]. URL: http://www. cs. ucsd. edu/users/elkan/clresults. html.
  • 7Merz C J, Merphy P. UCI repository of machine learning databases [EB/OL]. URL: http://www. ics. uci. edu/mlearn/MLRRepository. html.
  • 8HanJiawei MichelineKambe.数据挖掘概念与技术[M].北京:机械工业出版社,2001..
  • 9Lee W,Stolfo S J.Data Mining Approaches for Intrusion Detection[C].Proceeding of the 1998 USENIX Security Symposium,Texas:USENIX Association,1998:79-94.
  • 10KDD99.KDD99 Cup Dataset[DB/OL].http://kdd.ics.uci.edu/databases/kddcup99,1999.

共引文献70

同被引文献2

引证文献1

二级引证文献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