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Domain generation algorithms (DGAs) are commonly used by botnets to generate domain names that bots can use to establish communication channels with their command and control servers. Recent publications presented deep learning classifiers that detect algorithmically generated domain (AGD) names in real time with high accuracy and thus significantly reduce the effectiveness of DGAs for botnet communication. In this paper, we present MaskDGA, an evasion technique that uses adversarial learningdoi:10.1109/access.2020.3020964 fatcat:ejlsh37imzgz3kbic2o3lqyoii