The Rise of Deep Learning for Detection and Classification of Malware


Figure 1: CNNs on raw bytes for malware detection and classification

Artificial Intelligence (AI) continues to evolve and has made huge progress over the last decade. AI shapes our daily lives. Deep learning is a subset of techniques in AI that extract patterns from data using neural networks. Deep learning has been applied to image segmentation, protein structure, machine translation, speech recognition and robotics. It has outperformed human champions in the game of Go. In recent years, deep learning has been applied to malware analysis. Different types of deep learning algorithms, such as convolutional neural networks (CNN), recurrent neural networks and Feed-Forward networks, have been applied to a variety of use cases in malware analysis using bytes sequence, gray-scale image, structural entropy, API call sequence, HTTP traffic and network behavior.  

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