Enhance Domain-Invariant Transferability of Adversarial Examples via Distance Metric Attack

Enhance Domain-Invariant Transferability of Adversarial Examples via Distance Metric Attack

A general foundation of fooling a neural network without knowing the details (i.e., black-box attack) is the attack transferability of adversarial examples across different models. Many works have been devoted to enhancing the task-specific transferability of adversarial examples, whereas the cross-...

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Bibliographic Details
Main Authors:	Jin Zhang, Wenyu Peng, Ruxin Wang, Yu Lin, Wei Zhou, Ge Lan
Format:	Article
Language:	English
Published:	MDPI AG 2022-04-01
Series:	Mathematics
Subjects:	deep learning distance metric adversarial attack cross-task transferability
Online Access:	https://www.mdpi.com/2227-7390/10/8/1249

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