DETECTING AND MITIGATING MALICIOUS SOFTWARE CODE EMBEDDED IN IMAGE FILES USING MACHINE LEARNING TECHNIQUES

摘要

Techniques are provided for detecting malicious software code embedded in image files, using machine learning. One method comprises obtaining metadata for an image file; applying the obtained metadata to at least one machine learning technique to classify the image file into at least one of a plurality of predefined classes, wherein the plurality of predefined classes comprises at least one malicious file class; and determining whether the image file comprises malicious software code based on the classification. The machine learning technique is trained using image files classified into at least one of the plurality of predefined classes. The machine learning technique employs a deep neural network and/or a convolutional neural network to classify the image file into the at least one predefined class.