计算机科学 ›› 2007, Vol. 34 ›› Issue (9): 87-89.

• 软件工程与数据库技术 • 上一篇    下一篇

基于推进贝叶斯分类法的入侵检测引擎研究

张元清 包骏杰   

  1. 重庆教育学院计算机与现代教育技术系,重庆400067
  • 出版日期:2018-11-16 发布日期:2018-11-16

ZHANG Yuan-Qing, BAO Jun-Jie (Department of Computer and Modern Education Technology,Chongqing Education Collage, Chongqing 400067)   

  • Online:2018-11-16 Published:2018-11-16

摘要: 为了提高贝叶斯分类法的准确率,设计了基于推进技术的贝叶斯分类法,并将推进贝叶斯分类法应用到入侵检测引擎中,并设计了基于推进贝叶斯分类的入侵检测引擎。通过实验表明,此检测引擎可以有效的将入侵行为与非入侵行为进行分类,与传统贝叶斯分类法的检测引擎相比,此引擎对数据的分类有更高的准确率。

关键词: 入侵检测 数据挖掘 贝叶斯 推进

Abstract: To improve the accurate of Bayesian algorithm, a new Bayesian classification algorithm which based boosting was designed. The new Bayesian algorithm had been used in Intrusion Detection System, and an engine of Intrusion Detection System based the algorit

Key words: Intrusion detection, Data mining, Bayesian, Boosting

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