25 citations · 63 across the 7 of their papers we have counts for
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cs.CR2023★ 12 cited
ModelObfuscator: Obfuscating Model Information to Protect Deployed ML-based Systems
Mingyi Zhou, Xiang Gao, Jing Wu +4
More and more edge devices and mobile apps are leveraging deep learning (DL) capabilities. Deploying such models on devices -- referred to as on-device models -- rather than as rem…
cs.CR2020
Adversarial Imitation Attack
Mingyi Zhou, Jing Wu, Yipeng Liu +4
Deep learning models are known to be vulnerable to adversarial examples. A practical adversarial attack should require as little as possible knowledge of attacked models. Current s…
cs.CR2020★ 13 cited
DaST: Data-free Substitute Training for Adversarial Attacks
Mingyi Zhou, Jing Wu, Yipeng Liu +2
Machine learning models are vulnerable to adversarial examples. For the black-box setting, current substitute attacks need pre-trained models to generate adversarial examples. Howe…