In this study, we propose a method for generating mutated Windows malware against malware detection based on ensemble learning by combining GANs and RL to overcome the limitations of the MalGAN model.
Nội dung trích xuất từ tài liệu:
A method of generating mutated Windows malware to evade ensemble learning-based detectors
A method of generating mutated Windows malware to evade ensemble learning-based detectors
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Tìm kiếm theo từ khóa liên quan:
Information security Evasion attack Adversarial attack Malware mutation Generative adversarial networks Reinforcement learning Ensemble learningTài liệu có liên quan:
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