An Ensemble of Pre-trained Transformer Models For Imbalanced Multiclass Malware Classification. (arXiv:2112.13236v2 [cs.CR] UPDATED)

Classification of malware families is crucial for a comprehensive
understanding of how they can infect devices, computers, or systems. Thus,
malware identification enables security researchers and incident responders to
take precautions against malware and accelerate mitigation. API call sequences
made by malware are widely utilized features by machine and deep learning
models for malware classification as these sequences represent the behavior of
malware. However, traditional machine and deep learning models remain incapable
of capturing sequence relationships between API calls. On …

classification malware