Feature-space Bayesian adversarial learning improved malware detector robustness
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A novel method for improving the robustness of deep learning-based malware detectors against adversarial attacks
AbstractMalware is constantly evolving with rising concern for cyberspace. Deep learning-based malware detectors are being used as a potential solution. However, these detectors are vulnerable to adversarial attacks. The adversarial attacks manipulate ...
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Highlights- An approach to combining adversarial attacks is proposed to analyse the robustness of malware detectors against attacks.
- Ten adversarial attacks are created to generate binary-encoded malicious samples, including the proposed combined ...
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