Adversarial Attack on Attackers: Post-Process to Mitigate Black-Box Score-Based Query Attacks. (arXiv:2205.12134v1 [cs.LG])

The score-based query attacks (SQAs) pose practical threats to deep neural
networks by crafting adversarial perturbations within dozens of queries, only
using the model's output scores. Nonetheless, we note that if the loss trend of
the outputs is slightly perturbed, SQAs could be easily misled and thereby
become much less effective. Following this idea, we propose a novel defense,
namely Adversarial Attack on Attackers (AAA), to confound SQAs towards
incorrect attack directions by slightly modifying the output logits. In this …

adversarial attack attackers attacks box lg process score