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cs.CR2021
EG-Booster: Explanation-Guided Booster of ML Evasion Attacks
Abderrahmen Amich, Birhanu Eshete
The widespread usage of machine learning (ML) in a myriad of domains has raised questions about its trustworthiness in security-critical environments. Part of the quest for trustwo…
cs.LG2021★ 22 cited
Morphence: Moving Target Defense Against Adversarial Examples
Abderrahmen Amich, Birhanu Eshete
Robustness to adversarial examples of machine learning models remains an open topic of research. Attacks often succeed by repeatedly probing a fixed target model with adversarial e…
cs.CR2021
Explanation-Guided Diagnosis of Machine Learning Evasion Attacks
Abderrahmen Amich, Birhanu Eshete
Machine Learning (ML) models are susceptible to evasion attacks. Evasion accuracy is typically assessed using aggregate evasion rate, and it is an open question whether aggregate e…