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异常检测模式性能评估技术研究

Researching on the Evaluation Techn iques of Anomaly Detection Patterns Performance
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摘要 在对现有异常检测模式性能评估技术分析的基础上,给出一种基于理想异常检测临界值的异常检测模式性能评估方法,从而进一步增强了异常检测模式性能评估技术。 In this paper,we firstly analyze the ex isted performance evaluating techniques of ADP(Anomaly Detection Pat-terns)an d then present an ADP performance e valuating approach based on the Perfect-AD P,which reinforces the evalu ating techniques of ADP.
出处 《通信技术》 2003年第8期89-90,共2页 Communications Technology
关键词 异常检测 入侵检测 计算机安全 anomaly dete ction,intrusion detection,computer security
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参考文献4

  • 1[1]Dietterich T G. Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms. Neural Computation, 1998
  • 2[2]Portnoy L, Eskin E, Stolfo S J. Intrusion Detection with Unlabeled Data Using Clustering. In Proceedings of ACM CSS Workshop on Data Mining Applied to Security (DMSA - 2001 ), Philadelphia, PA, 2001
  • 3[3]Provost F, Fawcett T, Kohavi R. The Case Against Accuracy Estimation For Comparing Induction Algorithms. In Proceedings of the 15th International Conference on Machine Learning, July 1998
  • 4[4]Eskin E, Arnold A, Prerau M, etc. A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data. Data Mining for Security Applications, Kluwer 2002

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