An assessment of automatic speaker verification vulnerabilities to replay spoofing attacks

This paper analyses the threat of replay spoofing or presentation attacks in the context of automatic speaker verification. As relatively high-technology attacks, speech synthesis and voice conversion, which have thus far received far greater attention in the literature, are probably beyond the means of the average fraudster. The implementation of replay attacks, in contrast, requires no specific expertise nor sophisticated equipment. Replay attacks are thus likely to be the most prolific in practice, while their impact is relatively under-researched. The work presented here aims to compare at a high level the threat of replay attacks with those of speech synthesis and voice conversion. The comparison is performed using strictly controlled protocols and with six different automatic speaker verification systems including a state-of-the-art iVector/probabilistic linear discriminant analysis system. Experiments show that low-effort replay attacks present at least a comparable threat to speech synthesis and voice conversion. The paper also describes and assesses two replay attack countermeasures. A relatively new approach based on the local binary pattern analysis of speech spectrograms is shown to outperform a competing approach based on the detection of far-field recordings. Copyright (c) 2016 John Wiley & Sons, Ltd.