AI RESEARCH
FARM: Few-shot Adaptive Malware Family Classification under Concept Drift
arXiv CS.LG
•
ArXi:2601.17907v2 Announce Type: replace-cross Malware classification models often suffer performance degradation under concept drift due to evolving threat landscapes and the emergence of novel malware families. This paper presents FARM (Few-shot Adaptive Recognition of Malware), a unified framework for detecting and adapting to both covariate drift and label drift in Windows Portable Executable (PE) malware family classification.