Markov Image with Transfer Learning for Malware Detection and Classification

Abstract

Malware attack is a severe problem that can cause a considerable loss. To prevent the malware attack, different malware detection and classification method have been implemented in recent years. This paper proposed a new method based on Markov image and transfer learning on machine learning. Also, an experience comparing the performance on malware detection and classification between the proposed and grayscale methods was done. The accuracy and loss of malware detection and classification by using the proposed method are 0.973 and 0.076, 0.987 and 0.062 respectively. The accuracy and loss of malware detection and classification using the grayscale method are 0.989 and 0.037, 0.973 and 0.202 respectively. Although the grayscale method has done better in malware detection, the proposed method's accuracy is over 0.97. Therefore, the result shows that the proposed method are suitable for malware detection and classification.