March 1, 2024, 5:44 a.m. | Sonal Joshi, Thomas Thebaud, Jes\'us Villalba, Najim Dehak

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.19355v1 Announce Type: cross
Abstract: Adversarial examples have proven to threaten speaker identification systems, and several countermeasures against them have been proposed. In this paper, we propose a method to detect the presence of adversarial examples, i.e., a binary classifier distinguishing between benign and adversarial examples. We build upon and extend previous work on attack type classification by exploring new architectures. Additionally, we introduce a method for identifying the victim model on which the adversarial attack is carried out. To …

abstract adversarial adversarial examples arxiv binary classification classifier cs.cr cs.lg cs.sd detection eess.as examples identification paper speaker speaker identification systems them type

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