TRConv: Multi-Platform Malware Classification via Target Regulated Convolutions

Malware is an important threat to digital workflow. Traditional malware modeling approaches focused on using hand-crafted features while recent approaches proved the necessity of using learning based methodologies. In this paper, we propose a novel opcode based methodology that additionally learns m...

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Detalles Bibliográficos

Principais autores:	Alper Egitmen, Ali Gokhan Yavuz, Sirma Yavuz
Formato:	Artigo
Idioma:	Inglês
Publicado:	IEEE 2024-01-01
Series:	IEEE Access
Assuntos:	Convolutional network opcode length malware and benign malware behaviour analysis
Acceso en liña:	https://ieeexplore.ieee.org/document/10531015/
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