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Found 5 papers, 3 papers with code
How to choose your best allies for a transferable attack?
The transferability of adversarial examples is a key issue in the security of deep neural networks.
FBI: Fingerprinting models with Benign Inputs
We achieve both goals by demonstrating that benign inputs, that are unmodified images, for instance, are sufficient material for both tasks.
Randomized Smoothing under Attack: How Good is it in Pratice?
We first formally highlight the mismatch between a theoretical certification and the practice of attacks on classifiers.
RoBIC: A benchmark suite for assessing classifiers robustness
Many defenses have emerged with the development of adversarial attacks.
SurFree: a fast surrogate-free black-box attack
This paper presents SurFree, a geometrical approach that achieves a similar drastic reduction in the amount of queries in the hardest setup: black box decision-based attacks (only the top-1 label is available).
