Jan 29, 2023 · We design a new attack enhancement called \textit{Gradient Shaping} (GRASP), which follows the opposite direction of adversarial training to reduce the change ...
Feb 26, 2024 · This reverse-engineering step mostly relies on gradient descent, which seeks the greatest tendency towards misclassification following the ...
This reverse-engineering step mostly relies on gradient descent, which seeks the greatest tendency towards misclassification following the opposite direction of ...
Sep 28, 2024 · Gradient shaping: enhancing backdoor attack against reverse engineering. Open Webpage. Rui Zhu, Di Tang, Siyuan Tang, Zihao Wang, Guanhong Tao, Shiqing Ma.
Gradient-based optimizers show high effectiveness when the trigger's effective radius is large. 2. The effective radius of existing backdoor attacks ...
Subpixel accuracy from one single input image can be obtained by approximating the gradient of the square local contrast with a piecewise linear func-tion.
Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering. Profile image of di tang di tang. 2023, arXiv (Cornell University). See full PDF
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Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering Rui Zhu, Di Tang, Siyuan Tang, Zihao Wang, Guanhong Tao, Shiqing Ma, XiaoFeng Wang ...
Mar 2, 2024 · Most existing methods to detect backdoored machine learning (ML) models take one of the two approaches: trigger inversion (aka. reverse ...
2023. Gradient Shaping: Enhancing Backdoor Attack against Reverse Engineering ... Understanding impacts of task similarity on backdoor attack and detection.