A malware visualization method based on transition probability matrix suitable for imbalanced family classification

A malware visualization method based on transition probabilities of malware operation codes to generate proper images with a uniform size as inputs for CNN models is proposed and could address problems concerning insufficient or imbalanced datasets, which may challenge the classification abilities of CNN models.