您当前所在位置: 首页 > 学者

郑庆华

  • 23浏览

  • 0点赞

  • 0收藏

  • 0分享

  • 75下载

  • 0评论

  • 引用

期刊论文

A Classified Method Based on Support Vector Machine for Grid Computing Intrusion Detection

郑庆华Qinghua Zheng Hui Li and Yun Xiao

H. Jin, Y. Pan, N. Xiao, and J. Sun (Eds.): GCC 2004, LNCS 3251, pp. 875-878, 2004.,-0001,():

URL:

摘要/描述

A novel ID method based on Support Vector Machine (SVM) is proposed to solve the classification problem for the large amount of raw intrusion event dataset of the grid computing environment. A new radial basic function (RBF), based on heterogeneous value difference metric (HVDM) of heterogeneous datasets, is developed. Two different types of SVM, Supervised C_SVM and unsupervised One_Class SVM algorithms with kernel function, are applied to detect the anomaly network connection records. The experimental results of our method on the corpus of data collected by Lincoln Labs at MIT for an intrusion detection system evaluation sponsored by the U.S. Defense Advanced Research Projects Agency (DARPA) shows that the proposed method is feasible and effective.

关键词:

版权说明:以下全部内容由郑庆华上传于   2005年12月22日 23时46分46秒,版权归本人所有。

我要评论

全部评论 0

本学者其他成果

    同领域成果