Unraveling Adversarial Examples against Speaker Identification -- Techniques for Attack Detection and Victim Model Classification

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 …

adversarial arxiv attack binary classification countermeasures cs.cr cs.lg cs.sd detect detection eess.as examples identification presence speaker systems techniques threaten victim