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Are Malware Detection Classifiers Adversarially Vulnerable to Actor-Critic based Evasion Attacks?
2022
EAI Endorsed Transactions on Scalable Information Systems
Android devices like smartphones and tablets have become immensely popular and are an integral part of our daily lives. However, it has also attracted malware developers to design android malware which have grown aggressively in the last few years. Research shows that machine learning, ensemble, and deep learning models can successfully be used to detect android malware. However, the robustness of these models against well-crafted adversarial samples is not well investigated. Therefore, we
doi:10.4108/eai.31-5-2022.174087
fatcat:42jftpdh35db7p4do6gnnlygny