Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (21): 154-156.DOI: 10.3778/j.issn.1002-8331.2008.21.043

• 机器学习 • Previous Articles     Next Articles

Application of one-class classifier with negatives in security audit data analysis

LI Jia-zhen,PAN Zhi-song,NI Gui-qiang,WANG Qiong   

  1. Institute of Command Automation,PLA University of Science and Technology,Nanjing 210007,China
  • Received:2008-04-30 Revised:2008-06-11 Online:2008-07-21 Published:2008-07-21
  • Contact: LI Jia-zhen

带野值的单类分类器在安全审计中的应用

李佳桢,潘志松,倪桂强,王 琼   

  1. 解放军理工大学 指挥自动化学院,南京 210007
  • 通讯作者: 李佳桢

Abstract: One-class classifier is currently a hot spot of pattern recognition field.One-class classifier with negatives is based on one-classifier,by leading into a few costful abnormal samples to reinforce the classification.This model applies to the problems handling the two kind data categories imbalances where positives more over than negatives.It is proposed in this paper that using support vector data description with negatives in security audit data analysis system.Through some experiments,it is proved to be more sensitive with exceptional samples,so it will be more valuable in practice.

Key words: one-class classifier, support vector data description, security audit

摘要: 单类分类器是当前模式识别领域的一个研究热点。带野值的单类分类器是在单类分类器的基础上,通过引入少量珍贵的异常样本(野值),以加强分类器的性能。该模型适用于处理正类样本数目远多于反类样本的两类数据类别不平衡问题。提出了将带野值的支持向量描述方法应用于安全审计数据分析中,并通过实验证实了该方法对异常样本更为敏感,具有良好的应用潜力。

关键词: 单类分类器, 支持向量数据描述, 安全审计