Learning Transferable Adversarial Examples via Ghost Networks

AAAI, pp. 11458-11465, 2020.

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Abstract:

Recent development of adversarial attacks has proven that ensemble-based methods outperform traditional, non-ensemble ones in black-box attack. However, these methods generally require a family of diverse models, and ensembling them together afterward, both of which are computationally expensive. In this paper, we propose Ghost Networks...More

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