Decision-Based Attack to Speaker Recognition System via Local Low-Frequency Perturbation
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DOI: 10.1109/lsp.2022.3183538
Abstract: Despite neural network-based speaker recognition systems (SRS) have enjoyed significant success, they are proved to be quite vulnerable to adversarial examples. In practice, the SRS model parameters are not always available. Attackers have to probe… read more here.
Keywords: speaker recognition; low frequency; decision based; perturbation ... See more keywords
Decision-Based Adversarial Attack With Frequency Mixup
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2022.3156809
Abstract: It has been widely observed that deep neural networks are highly vulnerable to adversarial examples. Decision-based attacks could generate adversarial examples based solely on top-1 labels returned by the target model. However, they typically make… read more here.
Keywords: mixup; frequency; detection; decision based ... See more keywords