ISAnWin: inductive generalized zero-shot learning using deep CNN for malware detection across windows and android platforms

Effective malware detection is critical to safeguarding digital ecosystems from evolving cyber threats. However, the scarcity of labeled training data, particularly for cross-family malware detection, poses a significant challenge. This research proposes a novel architecture ConvNet-6 to be used in...

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Detalhes bibliográficos

Principais autores:	Umm-e-Hani Tayyab, Faiza Babar Khan, Asifullah Khan, Muhammad Hanif Durad, Farrukh Aslam Khan, Aftab Ali
Formato:	Artigo
Idioma:	Inglês
Publicado em:	PeerJ Inc. 2024-12-01
coleção:	PeerJ Computer Science
Assuntos:	Malware detection PE malware Android malware End-point protection Artificial intelligence Deep learning
Acesso em linha:	https://peerj.com/articles/cs-2604.pdf
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