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The Application of Ensemble Classification Techniques in Network Intrusion Detection: a Review

Publish place: First National Conference on Advances in computer science and information retrieval approaches
Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
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لینک ثابت به این Paper:
https://civilica.com/doc/225879

شناسه ملی سند علمی:

BPJ01_624

تاریخ نمایه سازی: 29 دی 1392

Abstract:

The application of data mining techniques in intrusion detection has attracted considerable attention from the research community. Ensemble learning can be used as an effective classification technique for intrusion detection. In an ensemble classification system, different base classifiers are combined in order to obtain a classifier with higher performance. In this paper, the most successful ensemble techniques used in the field of intrusion detection are introduced and discussed. These ensemble techniques are categorized based on the main idea of the ensemble and similarities in implementation of the models. The goal of this review is to provide insight into the benefits of current ensemble methods and how they can increase the performance of intrusion detection.

Keywords:

Intrusion Detection , Data mining , Ensemble Classifier , Performance Measures

Authors

Mohammad Amini

Department of Information Technology, University of Qom, Qom, Iran

Jalal Rezaeenoor

Department of Information Technology, University of Qom, Qom, Iran

Esmaeil Hadavandi

Department of Information Technology, University of Qom, Qom, Iran

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