EFFECTIVENESS EVALUATION OF CLASSIFICATION TREE AND KULLBACK-LEIBLER DISTANCE-BASED ANOMALY INTRUSION DETECTION APPROACH

Authors

  • Veselina Jecheva
  • Evgeniya Nikolova

Keywords:

intrusion detection, anomaly based IDS, relative entropy, receiveroperating characteristic Curve, accuracy, Matthews correlation coefficient, error rate

Abstract

The purpose of the paper is to present some evaluations of the effectiveness of IDS based on the classification tree and Kullback-Leibler distance-based approach to anomaly-based intrusion detection. The most used methods for this evaluation are: accuracy, Matthews correlation coefficient and ROC curve

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Published

2018-05-30

Issue

Vol. 2 No. 2 (2013): Computer Sciences and Communications

Section

Computer Science and Communications - Reviewed Publications. ISSN: 1314-7846

License

Articles published in "Computer Science and Communications" Magazine are licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.  

How to Cite

EFFECTIVENESS EVALUATION OF CLASSIFICATION TREE AND KULLBACK-LEIBLER DISTANCE-BASED ANOMALY INTRUSION DETECTION APPROACH. (2018). COMPUTER SCIENCES AND COMMUNICATIONS, 2(2), 62-68. https://csc.bfu.bg/index.php/CSC/article/view/184

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