Marwan Albahar*, Mohammed Thanoon, Monaj Alzilai, Alaa Alrehily, Munirah Alfaar, Maimoona Algamdi, Norah Alassaf
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2181-2202, 2021, DOI:10.32604/cmc.2021.018260
Abstract Malicious Portable Document Format (PDF) files represent one of the largest threats in the computer security space. Significant research has been done using handwritten signatures and machine learning based on detection via manual feature extraction. These approaches are time consuming, require substantial prior knowledge, and the list of features must be updated with each newly discovered vulnerability individually. In this study, we propose two models for PDF malware detection. The first model is a convolutional neural network (CNN) integrated into a standard deviation based regularization model to detect malicious PDF documents. The second model is a support vector machine (SVM)… More >
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