Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection

Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection

Abstract Intrusion detection systems play a critical role in the mitigation of cyber-attacks on the Internet of Things (IoT) environment. Due to the integration of many devices within the IoT environment, a huge amount of data is generated. The generated data sets in most cases consist of irrelevant...

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Bibliographic Details
Main Authors: Elijah M. Maseno, Zenghui Wang
Format: Article
Language:English
Published: SpringerOpen 2024-02-01
Series:Journal of Big Data
Subjects:
Extreme learning machine
Genetic algorithm
Feature selection
Wrapper methods
IoT
ToN network data set
Online Access:https://doi.org/10.1186/s40537-024-00887-9

Internet

https://doi.org/10.1186/s40537-024-00887-9

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