Multi-class Malware Classification
Multi-Class Malware Classification is a malware analysis task that involves categorizing malicious software into one of several predefined distinct classes based on shared behavioral, structural, or code-level characteristics, distinguishing it from binary or hierarchical classification approaches by enabling fine-grained discrimination across multiple malware families simultaneously.
19
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842
Citations
82
Authors
37
Institutions
Publications per year
2017–2026
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Malware class recognition using image processing techniques
Aziz Makandar, Anita Patrot · 2017 · 106 citations
Using Multi-features and Ensemble Learning Method for Imbalanced Malware Classification
Yunan Zhang, Qingjia Huang, Xinjian Ma et al. · 2016 · 73 citations
Self-Supervised Vision Transformers for Malware Detection
Sachith Seneviratne, Ridwan Shariffdeen, Sanka Rasnayaka et al. · IEEE Access · 2022 · 67 citations · Full text
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Institute of Information Engineering
Beijing, China
3 h-index
13 publications
301 citations

Chinese Academy of Sciences
Beijing, China
2 h-index
10 publications
202 citations
Sukkur IBA University
Sukkur, Pakistan
2 h-index
3 publications
75 citations
Free University of Bozen-Bolzano
Bolzano, Italy
1 h-index
2 publications
50 citations
Jilian Technology Group (China)
Shanghai, China
1 h-index
1 publications
13 citations
University of Chinese Academy of Sciences
Beijing, China
1 h-index
4 publications
52 citations

American University of Beirut
Beirut, Lebanon
1 h-index
2 publications
34 citations

Thapar Institute of Engineering & Technology
Patiāla, India
1 h-index
2 publications
224 citations
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3 publications · 128 citations
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2 publications · 141 citations
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2 publications · 43 citations
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1 publications · 26 citations
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1 publications · 30 citations
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