search

fra31 / auto-attack

Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
https://arxiv.org/abs/2003.01690
MIT License
639 stars 111 forks source link

Fixed evaluation of models with random defenses #105

Open Buntender opened 7 months ago

Buntender commented 7 months ago

Thank you for your outstanding contributions.

@LYMDLUT and I put forward this PR to improve the evaluation of models with random defenses.

We've noticed that AutoAttack's current strategy for selecting the final output (clean/APGD etc) based on one time evaluation, regardless of whether the target models implement random defenses or not. This overlooks the variability of outputs in models with random defenses.

Relying on a single evaluation to filter samples for subsequent attacks leads to inflated success rate and hinders the exploration of attack methods that could potentially yield superior outcomes.

To address this, we propose to perform multiple time evaluations for models with random defenses and chose the adversarial example with the highest robustness as final output.

LYMDLUT commented 5 months ago

@fra31 Could you please review this pr？

ScarlettChan commented 5 months ago

您好，您的邮件已收到!