A Hybrid Method Using Slime Mold Algorithm and Genetic Algorithm for Feature Selection Problems in Intrusion Detection Systems

A Hybrid Method Using Slime Mold Algorithm and Genetic Algorithm for Feature Selection Problems in Intrusion Detection Systems

ABSTRACT This paper presents an innovative hybrid approach for intrusion detection system (IDS) proposed by integrating the slime mold algorithm (SMA) and genetic algorithm (GA) within a feature selection (FS) framework for classification tasks. IDS faces challenges such as high‐dimensional data and...

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Bibliographic Details
Main Authors: Soodeh Hosseini, Mahdieh Khorashadizade, Morteza Jouyban
Format: Article
Language:English
Published: Wiley 2025-07-01
Series:Engineering Reports
Subjects:
classification problems
feature selection (FS)
intrusion detection system (IDS)
metaheuristic algorithm (MA)
Online Access:https://doi.org/10.1002/eng2.70254
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