Proving Common Mechanisms Shared by Twelve Methods of Boosting
Adversarial Transferability
- URL: http://arxiv.org/abs/2207.11694v1
- Date: Sun, 24 Jul 2022 08:36:12 GMT
- Title: Proving Common Mechanisms Shared by Twelve Methods of Boosting
Adversarial Transferability
- Authors: Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang,
Xiangming Zhu
- Abstract summary: This paper summarizes the common mechanism shared by twelve previous transferability-boosting methods in a unified view.
We first discover and prove the negative correlation between the adversarial transferability and the attacking utility of interactions.
More crucially, we consider the reduction of interactions as the essential reason for the enhancement of adversarial transferability.
- Score: 39.82790215086004
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Although many methods have been proposed to enhance the transferability of
adversarial perturbations, these methods are designed in a heuristic manner,
and the essential mechanism for improving adversarial transferability is still
unclear. This paper summarizes the common mechanism shared by twelve previous
transferability-boosting methods in a unified view, i.e., these methods all
reduce game-theoretic interactions between regional adversarial perturbations.
To this end, we focus on the attacking utility of all interactions between
regional adversarial perturbations, and we first discover and prove the
negative correlation between the adversarial transferability and the attacking
utility of interactions. Based on this discovery, we theoretically prove and
empirically verify that twelve previous transferability-boosting methods all
reduce interactions between regional adversarial perturbations. More crucially,
we consider the reduction of interactions as the essential reason for the
enhancement of adversarial transferability. Furthermore, we design the
interaction loss to directly penalize interactions between regional adversarial
perturbations during attacking. Experimental results show that the interaction
loss significantly improves the transferability of adversarial perturbations.
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