Stealthy and robust backdoor attack on deep neural networks based on data augmentation
This work proposes to use data augmentation for backdoor attacks to increase the stealth, attack success rate, and robustness. Different data augmentation techniques are applied independently on three color channels to embed a composite trigger. The data augmentation strength is tuned based on the G...
| Autors principals: | , |
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| Altres autors: | |
| Format: | Conference Paper |
| Idioma: | English |
| Publicat: |
2024
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| Accés en línia: | https://hdl.handle.net/10356/174145 https://ieee-ceda.org/event/2022-asian-hardware-oriented-security-and-trust-symposium |