Dual-Channel Mamba-Based Semantic–Behavioral Feature Learning with Prototype-Guided Zero-Shot Inference for Zero-Day Malware Detection

Detecting previously unseen malware remains a critical challenge for modern cybersecurity systems due to the rapid evolution of malicious software and the limitations of traditional supervised detection models. This paper proposes a Dual-Channel Mamba-Based Semantic–Behavioral Feature Learning frame...

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Autors principals:	Ahmed Essaa Abed Alowaidi, Galip Cansever
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-05-01
Col·lecció:	Applied Sciences
Matèries:	zero-day malware detection mamba architecture semantic–behavioral feature learning prototype-based zero-shot inference malware analysis
Accés en línia:	https://www.mdpi.com/2076-3417/16/11/5326
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Dual-Channel Mamba-Based Semantic–Behavioral Feature Learning with Prototype-Guided Zero-Shot Inference for Zero-Day Malware Detection

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