Advancements in Voice Spoofing Detection: A Comprehensive ‎Review

  • Authors

    • Rekha Rani Research Scholar, Department of Computer Science & Applications, Maharshi Dayanand ‎University, Rohtak, Haryana, India
    • Bal Kishan Associate Professor, Department of Computer Science & Applications, Maharshi Dayanand ‎University, Rohtak, Haryana, India
    https://doi.org/10.14419/w36qrh81

    Received date: July 13, 2025

    Accepted date: August 27, 2025

    Published date: September 7, 2025

  • ASV; Spoofing Attacks; Adversarial Attack; Machine Learning; Countermeasures

  • Abstract

    The reliability of voice-based authentication has increased with the adoption of voice-controlled technologies ‎and digital transactions. Automatic Speaker Verification (ASV) provides a dependable approach due to its ‎special capacity to confirm identity based on speech. ASV is mostly used in telecommunications, banking, law ‎enforcement, and smart assistants to increase security and user comfort. However, spoofing attacks like voice ‎conversion and speech synthesis are increasingly targeting these systems, making them less compatible, ‎examining responses to new kinds of attacks through data augmentation, and highlighting the role of transfer ‎learning in improving detection even when there is a lack of data. This review discusses the importance of ‎strengthening ASV systems with data augmentation to address new threats, transfer learning to enhance ‎detection with limited data, and adaptive models to keep up with advancing spoofing attacks‎.

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  • How to Cite

    Rani, R., & Kishan , B. . (2025). Advancements in Voice Spoofing Detection: A Comprehensive ‎Review. International Journal of Basic and Applied Sciences, 14(5), 224-235. https://doi.org/10.14419/w36qrh81