Adversarial Deep Ensemble: Evasion Attacks and Defenses for Malware Detection

Published: Jun 30, 2020
Abstract
Malware remains a big threat to cyber security, calling for machine learning based malware detection. While promising, such detectors are known to be vulnerable to evasion attacks. Ensemble learning typically facilitates countermeasures, while attackers can leverage this technique to improve attack effectiveness as well. This motivates us to investigate which kind of robustness the ensemble defense or effectiveness the ensemble attack can...
Paper Details
Title
Adversarial Deep Ensemble: Evasion Attacks and Defenses for Malware Detection
Published Date
Jun 30, 2020
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