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AED-PADA:Improving Generalizability of Adversarial Example Detection via Principal Adversarial Domain Adaptation
April 22, 2024, 4:42 a.m. | Heqi Peng, Yunhong Wang, Ruijie Yang, Beichen Li, Rui Wang, Yuanfang Guo
cs.LG updates on arXiv.org arxiv.org
Abstract: Adversarial example detection, which can be conveniently applied in many scenarios, is important in the area of adversarial defense. Unfortunately, existing detection methods suffer from poor generalization performance, because their training process usually relies on the examples generated from a single known adversarial attack and there exists a large discrepancy between the training and unseen testing adversarial examples. To address this issue, we propose a novel method, named Adversarial Example Detection via Principal Adversarial Domain …
abstract adversarial arxiv cs.cr cs.cv cs.lg defense detection detection methods domain domain adaptation example examples generated improving performance process training type via
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