GANBA: Generative Adversarial Network for Biometric Anti-Spoofing
نویسندگان
چکیده
Automatic speaker verification (ASV) is a voice biometric technology whose security might be compromised by spoofing attacks. To increase the robustness against attacks, presentation attack detection (PAD) or anti-spoofing systems for detecting replay, text-to-speech and conversion-based attacks are being developed. However, it was recently shown that adversarial may seriously fool systems. Moreover, of whole system (ASV + PAD) this new type completely unexplored. In work, generative network (GANBA) proposed. GANBA has twofold basis: (1) jointly employs ASV losses to yield very damaging (2) trains PAD as discriminator in order make them more robust these types The proposed able generate which can complete system. Then, resulting discriminators used defense technique both original physical access (PA) logical (LA) scenarios ASVspoof 2019 database were employed carry out experiments. experimental results show quite effective, outperforming other techniques when applied white-box black-box setups. addition,
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2022
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app12031454