Stealthy and robust backdoor attack on deep neural networks based on data augmentation

• المؤلفون الرئيسيون: Xu, Chaohui, Chang, Chip Hong
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2024
• الموضوعات: Engineering; Deep neural networks; Data augmentation
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/174145; https://ieee-ceda.org/event/2022-asian-hardware-oriented-security-and-trust-symposium

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...