How to choose your best allies for a transferable attack?. (arXiv:2304.02312v1 [cs.CR])

The transferability of adversarial examples is a key issue in the security of
deep neural networks. The possibility of an adversarial example crafted for a
source model fooling another targeted model makes the threat of adversarial
attacks more realistic. Measuring transferability is a crucial problem, but the
Attack Success Rate alone does not provide a sound evaluation. This paper
proposes a new methodology for evaluating transferability by putting distortion
in a central position. This new tool shows that transferable attacks …

adversarial adversarial attacks attack attacks black box box evaluation issue key may measuring networks neural networks problem rate security sound threat tool