LiVoAuth: Liveness Detection in Voiceprint Authentication with Random Challenges and Detection Modes

R. Zhang, Z. Yan, X. Wang, R. H. Deng

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
71 Downloads (Pure)

Abstract

Voiceprint authentication provides great convenience to users in many application scenarios. However, it easily suffers from spoofing attacks including speech synthesis, speech conversion, and speech replay. Liveness detection is an effective way to resist these attacks. But existing methods suffer from many disadvantages, such as extra deployment costs due to precise data collection, environmental disturbance, high computational overhead, and operational complexity. A uniform platform that can offer voiceprint authentication as a service (VAaS) over the cloud is also lacked. Hence, it is imperative to design an economic and effective method for liveness detection in voiceprint authentication. In this article, we propose a novel liveness detection method named LiVoAuth for voiceprint authentication. It applies a randomly generated vector sequence as liveness detection mode (LDM), corresponding to a random challenge code used for authentication. We implement LiVoAuth and conduct a series of user studies to evaluate its performance in terms of accuracy, stability, efficiency, security, and user acceptance.

Original languageEnglish
Pages (from-to)7676-7688
Number of pages13
JournalIEEE Transactions on Industrial Informatics
Volume19
Issue number6
Early online date2022
DOIs
Publication statusPublished - Jun 2023
MoE publication typeA1 Journal article-refereed

Keywords

  • Spectrogram
  • Authentication
  • Speech recognition
  • Codes
  • Usability
  • Microphones
  • Feature extraction
  • Identity Authentication
  • Voiceprint Recog- nition
  • Spoofing Attack
  • Liveness Detection

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