research-article

Spoofing and countermeasures for speaker verification

Authors:

Nicholas Evans,

Junichi Yamagishi,

Federico Alegre,

Haizhou LiAuthors Info & Claims

Speech Communication, Volume 66, Issue C

Pages 130 - 153

https://doi.org/10.1016/j.specom.2014.10.005

Published: 01 February 2015 Publication History

Abstract

While biometric authentication has advanced significantly in recent years, evidence shows the technology can be susceptible to malicious spoofing attacks. The research community has responded with dedicated countermeasures which aim to detect and deflect such attacks. Even if the literature shows that they can be effective, the problem is far from being solved; biometric systems remain vulnerable to spoofing. Despite a growing momentum to develop spoofing countermeasures for automatic speaker verification, now that the technology has matured sufficiently to support mass deployment in an array of diverse applications, greater effort will be needed in the future to ensure adequate protection against spoofing. This article provides a survey of past work and identifies priority research directions for the future. We summarise previous studies involving impersonation, replay, speech synthesis and voice conversion spoofing attacks and more recent efforts to develop dedicated countermeasures. The survey shows that future research should address the lack of standard datasets and the over-fitting of existing countermeasures to specific, known spoofing attacks.

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cover image Speech Communication

Speech Communication Volume 66, Issue C

February 2015

243 pages

ISSN:0167-6393

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Copyright © Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 February 2015

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Mahum RIrtaza AJaved AMahmoud HHassan H(2024)DeepDet: YAMNet with BottleNeck Attention Module (BAM) for TTS synthesis detectionEURASIP Journal on Audio, Speech, and Music Processing10.1186/s13636-024-00335-92024:1Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1186/s13636-024-00335-9
Yan BLan JYan Z(2024)Backdoor Attacks against Voice Recognition Systems: A SurveyACM Computing Surveys10.1145/370198557:3(1-35)Online publication date: 22-Nov-2024
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Gu HYi JWang CRen YTao JYan XChen YZhang XCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)Utilizing Speaker Profiles for Impersonation Audio DetectionProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681602(1961-1970)Online publication date: 28-Oct-2024
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Han CMitra PBillah S(2024)Uncovering Human Traits in Determining Real and Spoofed Audio: Insights from Blind and Sighted IndividualsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642817(1-14)Online publication date: 11-May-2024
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Paul ASharma VOlukoya O(2024)SQL injection attackJournal of Information Security and Applications10.1016/j.jisa.2024.10387185:COnline publication date: 1-Sep-2024
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