Detecção de tentativa de invasão por dados sintéticos em aplicações de biometria por voz

  • Wilson Neto UEA
  • Carlos Figueiredo UEA


Sistemas de biometrias baseados em voz são muito comuns hoje em dia, principalmente com a popularização de sistemas de comando por voz e assistentes digitais, como Google Assistant ou Alexa. Uma funcionalidade importante desses sistemas é detectar o usuário que está emitindo um comando, pois, assim controla-se o acesso à informações pessoais ou sensı́veis ao seu perfil. Assim, como em biometria baseada em faces, biometria por áudio pode sofrer ataques por dados sintéticos, onde gravações podem se fazer passar por dados reais. Este trabalho apresenta um modelo baseado em redes neurais profundas capaz de detectar essa técnica de invasão. Para o treinamento utilizou-se dados reais de gravações e dados sintéticos gerados a partir das gravações originais. Obteve-se resultados condizentes com a literatura, principalmente pela baixa taxa de falsa aceitação e alta taxa de F1-Score, mesmo em diferentes ambientes e ruı́dos.

Palavras-chave: anti-spoofing, synthetic data, synthetic audio, biometric system


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NETO, Wilson; FIGUEIREDO, Carlos . Detecção de tentativa de invasão por dados sintéticos em aplicações de biometria por voz. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 11. , 2019, Belém. Anais do XI Simpósio Brasileiro de Computação Ubíqua e Pervasiva. Porto Alegre: Sociedade Brasileira de Computação, july 2019 . ISSN 2595-6183. DOI: