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基于组合分类器的校园网入侵检测

Intrusion Detection of Campus Network Based on Combined Classifier
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摘要 为了增强校园网络的安全性,提出KPCA和BP神经网络相结合的组合分类器法构造入侵检测系统.先用KPCA对原始数据进行降维处理,而后用BP神经网络对新的数据进行分类检测.结果表明,该方法能有效地缩短检测时间,提高检测效率. To improve safety of campus network,an intrusion detection system is proposed by combined classifier which is combination of KPCA technology and BP Neural Network.First,KPCA technology is used to decrease the dimensions of raw data,and then the new data samples are classified by BP neural network.Results show that the method can shorten detection time and enhance detection rate.
作者 周宓
出处 《新乡学院学报》 2012年第5期421-422,425,共3页 Journal of Xinxiang University
关键词 KPCA BP 神经网络 入侵检测 检测时间 KPCA BP neural network intrusion detection detection time
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  • 1郭辉,王玲,刘贺平.基于核主成分分析与最小二乘支持向量机结合处理时间序列预测问题[J].北京科技大学学报,2006,28(3):303-306. 被引量:14
  • 2陈谊.分布式虚拟环境中的一致性问题研究[J].计算机工程,2007,33(12):60-62. 被引量:4
  • 3Ian F, Kesselman C, Jeffrey M. Grid services for distributed system integration[J]. Computer, 2002, 35(6) : 37 - 46. 被引量:1
  • 4Zhu Sui-hui, Du Zhi-hui, Chai Xu-dong. GDSA: A Grid-based Distributed Simulation Architecture[ C]//Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid Workshops, USA, 2006. 被引量:1
  • 5Foster I, Kesselman C, Tuecke S. The anatomy of the grid: enabling scalable virtual organizations[J]. International Journal of High Performance Computing Applications, 2001, 15(3) : 200 - 222. 被引量:1
  • 6Bernhard Sch(o)lkopf,Alexander J.Smola,Klaus-Robert Müller.Kernel Principal Component Analysis[J].Neural Comput,1998,12(10):1299-1293. 被引量:1
  • 7CAO L J,CHUA K S,CHONG W K.A Comparison of PCA,KPCA,and ICA for Dimensionality Reduction in Support Vector Machine[J].Neuro-computing,2003,55(2):321-336. 被引量:1
  • 8FUNG G,MANGASARIAN O L.Proximal Support Vector Machine Classifiers[R].Data Mining InstituteTechnical Report 01-02,Februray 2001.Proceedings of KDD-2001,San Francisco,August 2629,.Association for Computing Machinery,New York,2001:77-86. 被引量:1
  • 9LEE Y J,MANGASARIAN O L.RSVM:Reduced Support Vector Machines[R].Data Mining Institute Technical Report 00-07,July 2000.Proceedings of the First SIAM International Conference on Data Mining,Chicago,April 527,2001,SIAM,Philadelphia,CD-ROM Proceeding. 被引量:1
  • 10FUNG G, MANGASARIAN O L. Proximal support vector machine classifiers [EB/OL]. [2001-02-05] http:// www. cs. wise. edu/pub/dmi/tech-reports/01- 02. ps. 被引量:1

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