An Explainable Hybrid Pipeline for Malware Classification: Benchmark Construction, Feature Reduction, and Security-Oriented Evaluation

Malware classification increasingly relies on machine learning models that combine static and dynamic evidence, yet their practical use is often limited by dataset inconsistency, high-dimensional feature spaces, and insufficient transparency. This paper presents an explainable hybrid malware-classif...

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Principais autores:	Carmelo Ardito, Giuseppe Loseto, Riccardo Di Pietro, Nicola Epicoco, Alessandro Massaro
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2026-06-01
Series:	Journal of Cybersecurity and Privacy
Assuntos:	malware classification explainable AI hybrid malware analysis feature reduction security-oriented evaluation
Acceso en liña:	https://www.mdpi.com/2624-800X/6/3/105
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