An Enhanced Anomaly Detection in Web Traffic Using a Stack of Classifier Ensemble

An Enhanced Anomaly Detection in Web Traffic Using a Stack of Classifier Ensemble

A Web attack protection system is extremely essential in today's information age. Classifier ensembles have been considered for anomaly-based intrusion detection in Web traffic. However, they suffer from an unsatisfactory performance due to a poor ensemble design. This paper proposes a stacked...

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Bibliographic Details
Main Authors: Bayu Adhi Tama, Lewis Nkenyereye, S.M. Riazul Islam, Kyung-Sup Kwak
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Random forest
gradient boosting machine
Web attack
performance benchmark
anomaly-based IDSs
significance tests
Online Access:https://ieeexplore.ieee.org/document/8981962/

Internet

https://ieeexplore.ieee.org/document/8981962/

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