Attention-Based Cross-Modal CNN Using Non-Disassembled Files for Malware Classification

Attention-Based Cross-Modal CNN Using Non-Disassembled Files for Malware Classification

The role of malware classification is crucial in addressing the explosive increase in malware variants. By classifying malware instances into malware families, malware analysts can apply appropriate techniques and tools to handle malware variants in each family. Using high-level representations of m...

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Bibliographic Details
Main Authors: Jeongwoo Kim, Joon-Young Paik, Eun-Sun Cho
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Malware classification
structural entropy
malware image
deep learning
convolutional neural network
attention mechanism
Online Access:https://ieeexplore.ieee.org/document/10061401/

Internet

https://ieeexplore.ieee.org/document/10061401/

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