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...

Descrizione completa

Dettagli Bibliografici

Autori principali:	Carmelo Ardito, Giuseppe Loseto, Riccardo Di Pietro, Nicola Epicoco, Alessandro Massaro
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2026-06-01
Serie:	Journal of Cybersecurity and Privacy
Soggetti:	malware classification explainable AI hybrid malware analysis feature reduction security-oriented evaluation
Accesso online:	https://www.mdpi.com/2624-800X/6/3/105
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!