Feature Selection Methods Simultaneously Improve the Detection Accuracy and Model Building Time of Machine Learning Classifiers

Feature Selection Methods Simultaneously Improve the Detection Accuracy and Model Building Time of Machine Learning Classifiers

The detection accuracy and model building time of machine learning (ML) classifiers are vital aspects for an intrusion detection system (IDS) to predict attacks in real life. Recently, researchers have introduced feature selection methods to increase the detection accuracy and minimize the model bui...

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Bibliographic Details
Main Authors: Saleh Alabdulwahab, BongKyo Moon
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Symmetry
Subjects:
IDS
ML classifiers
information security
network
Weka
NSL-KDD
Online Access:https://www.mdpi.com/2073-8994/12/9/1424

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