Deep learning has been recently achieving a great performance for malware\nclassification task. Several research studies such as that of converting malware\ninto gray-scale images have helped to improve the task of classification in the\nsense that it is easier to use an image as input to a model that uses Deep\nLearning�s Convolutional Neural Network. In this paper, we propose a Convolutional\nNeural Network model for malware image classification that is able\nto reach 98% accuracy.
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