WitrynaExtensive experiments on ImageNet Dataset indicate that our proposed method could exhibit higher transferability and achieve higher attack success rates on both single model settings and ensemble-model settings. It can also combine with other gradient-based methods and image transformation-based methods to further build more … Witryna%0 Conference Paper %T Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks %A Lei Wu %A Zhanxing Zhu %B Proceedings of The 12th Asian Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2024 %E Sinno Jialin Pan %E Masashi Sugiyama …
Boosting the Transferability of Adversarial Attacks with Reverse ...
Witryna1 mar 2024 · Improving transferability of adversarial examples with powerful affine-shear transformation attack 1. Introduction. Image classification and recognition … WitrynaTWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization Ziquan Liu · Yi Xu · Xiangyang Ji · Antoni Chan … binding router bits
Improving Out-of-Distribution Generalization by Adversarial …
Witrynageneralization ability) of adversarial examples comes from the “linear nature” of modern DNNs. We conduct empirical study to try utilizing the hypothesis for improving the transferability in practice. We identify a non-trivial improvement by simply removing some of the nonlinear activations in a DNN, WitrynaThis work empirically investigates two classes of factors that might influence the transferability of adversarial examples, including model-specific factors, including network architecture, model capacity and test accuracy, and proposes a simple but effective strategy to improve the transferable. Currently it is well known that deep … WitrynaDeep neural networks(DNNs) is vulnerable to be attacked by adversarial examples. Black-box attack is the most threatening attack. At present, black-box attack methods ... cystotomy during hysterectomy