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Recently, convolutional neural networks (CNNs), a deep learning approach, have shown superior performance compared to traditional learning algorithms, especially in tasks such as image classification. Inspired by this, the authors propose a CNN-based architecture to classify malware samples. They convert malware binaries to grayscale images and subsequently train a CNN for classification. Experiments on two challenging malware classification datasets, namely Malimg and Microsoft, demonstrate that their method outperforms competing state-of-the-art algorithms.<\/jats:p>","DOI":"10.4018\/ijdcf.2020010105","type":"journal-article","created":{"date-parts":[[2019,10,22]],"date-time":"2019-10-22T16:03:55Z","timestamp":1571760235000},"page":"90-108","source":"Crossref","is-referenced-by-count":10,"title":["A Deep Learning Framework for Malware Classification"],"prefix":"10.4018","volume":"12","author":[{"given":"Mahmoud","family":"Kalash","sequence":"first","affiliation":[{"name":"University of Manitoba, Winnipeg, Canada"}]},{"given":"Mrigank","family":"Rochan","sequence":"additional","affiliation":[{"name":"University of Manitoba, Winnipeg, Canada"}]},{"given":"Noman","family":"Mohammed","sequence":"additional","affiliation":[{"name":"University of Manitoba, Winnipeg, Canada"}]},{"given":"Neil","family":"Bruce","sequence":"additional","affiliation":[{"name":"Ryerson University, Toronto, Canada"}]},{"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Manitoba, Winnipeg, Canada"}]},{"given":"Farkhund","family":"Iqbal","sequence":"additional","affiliation":[{"name":"Zayed University, Abu Dhabi, UAE"}]}],"member":"2432","reference":[{"key":"IJDCF.2020010105-0","doi-asserted-by":"publisher","DOI":"10.1145\/2857705.2857713"},{"key":"IJDCF.2020010105-1","author":"D.Arp","year":"2014","journal-title":"DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket"},{"key":"IJDCF.2020010105-2","author":"U.Bayer","year":"2009","journal-title":"Scalable, Behavior-Based Malware Clustering"},{"key":"IJDCF.2020010105-3","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"IJDCF.2020010105-4","unstructured":"Collobert, R., Kavukcuoglu, K., & Farabet, C. 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