Abstract: The potential for biometric systems to be manipulated through some form of subversion is well acknowledged. One such approach known as spoofing relates to the provocation of false accepts in authentication applications. Another approach referred to as obfuscation relates to the provocation of missed detections in surveillance applications. While the automatic speaker verification research community is now addressing spoofing and countermeasures, vulnerabilities to obfuscation remain largely unknown. This paper reports the first study. Our work with standard NIST datasets and protocols shows that the equal error rate of a standard GMM-UBM system is increased from 9% to 48% through obfuscation, whereas that of a state-of-the-art i-vector system increases from 3% to 20%. We also present a generalised approach to obfuscation detection which succeeds in detecting almost all attempts to evade detection.

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