ON THE VULNERABILITY OF AUTOMATIC SPEAKER RECOGNITION TO SPOOFING ATTACKS WITH ARTIFICIAL SIGNALS

Federico Alegre (1) , Ravichander Vipperla (1) , Nicholas Evans (1) , Benoît Fauve (2)

1 Eurecom [Sophia Antipolis]
2 ValidSoft UK Ltd

Automatic speaker verification (ASV) systems are increasingly being used for biometric authentication even if their vulnerability to imposture or spoofing is now widely acknowledged. Recent work has proposed different spoofing approaches which can be used to test vulnerabilities. This paper introduces a new approach based on artificial, tone-like signals which provoke higher ASV scores than genuine client tests. Experimental results show degradations in the equal error rate from 8.5% to 77.3% and from 4.8% to 64.3% for standard Gaussian mixture model and factor analysis based ASV systems respectively. These findings demonstrate the importance of efforts to develop dedicated countermeasures, some of them trivial, to protect ASV systems from spoofing.

Mots clés: biometrics; speaker verification; spoofing; imposture

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Federico Alegre, Ravichander Vipperla, Nicholas Evans, Benoît Fauve. ON THE VULNERABILITY OF AUTOMATIC SPEAKER RECOGNITION TO SPOOFING ATTACKS WITH ARTIFICIAL SIGNALS. EUSIPCO 2012, 20th European Signal Processing Conference, Aug 2012, Bucharest, Romania. ⟨hal-00783812⟩