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

• Main Authors: Xu, Chaohui, Chang, Chip Hong
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2024
• Subjects: Engineering; Deep neural networks; Data augmentation
• Online Access: https://hdl.handle.net/10356/174145; https://ieee-ceda.org/event/2022-asian-hardware-oriented-security-and-trust-symposium
• Institution: Nanyang Technological University

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...