Malware Classification System using Deep Learning Technique
Abstract - There has been a massive increase in the variety and volume of malware in recent years. This poses a serious security threat to major organisations and individuals. In order to combat the rapid growth of malware, it is essential to identify malware samples. This helps to effectively analyze large numbers of malware variants. The customary machine learning approaches often require a significant amount of resources in feature engineering. Recently, advanced machine learning such as deep learning have outperformed the conventional machine learning algorithms. Convolutional Neural Network (CNN), a deep learning approach, is found to be remarkable in image classification. In this paper, we employ Convolutional Neural Network algorithm to classify malware samples. We evaluated this technique on Malimg malware dataset and accomplished an accuracy of 95.73%.
Keywords - Malware classification, Obfuscation, Cyber security, Deep learning, Convolutional Neural Network.