Fuzziness-tuned: Improving the Transferability of Adversarial Examples. (arXiv:2303.10078v1 [cs.LG])

With the development of adversarial attacks, adversairal examples have been
widely used to enhance the robustness of the training models on deep neural
networks. Although considerable efforts of adversarial attacks on improving the
transferability of adversarial examples have been developed, the attack success
rate of the transfer-based attacks on the surrogate model is much higher than
that on victim model under the low attack strength (e.g., the attack strength
$\epsilon=8/255$). In this paper, we first systematically investigated this
issue and …

adversarial adversarial attacks attack attacks development higher low networks neural networks rate robustness strength training under victim