Overview of BTAS 2016 speaker anti-spoofing competition (original) (raw)
Related papers
Speaker Recognition Anti-spoofing
Advances in Computer Vision and Pattern Recognition, 2014
Progress in the development of spoofing countermeasures for automatic speaker recognition is less advanced than equivalent work related to other biometric modalities. This chapter outlines the potential for even state-of-the-art automatic speaker recognition systems to be spoofed. While the use of a multitude of different datasets, protocols and metrics complicates the meaningful comparison of different vulnerabilities, we review previous work related to impersonation, replay, speech synthesis and voice conversion spoofing attacks. The article also presents an analysis of the early work to develop spoofing countermeasures. The literature shows that there is significant potential for automatic speaker verification systems to be spoofed, that significant further work is required to develop generalised countermeasures, that there is a need for standard datasets, evaluation protocols and metrics and that greater emphasis should be placed on text-dependent scenarios.
ASVspoof: The Automatic Speaker Verification Spoofing and Countermeasures Challenge
IEEE Journal of Selected Topics in Signal Processing
Concerns regarding the vulnerability of automatic speaker verification (ASV) technology against spoofing can undermine confidence in its reliability and form a barrier to exploitation. The absence of competitive evaluations and the lack of common datasets has hampered progress in developing effective spoofing countermeasures. This paper describes the ASV Spoofing and Countermeasures (ASVspoof) initiative, which aims to fill this void. Through the provision of a common dataset, protocols, and metrics, ASVspoof promotes a sound research methodology and fosters technological progress. This paper also describes the ASVspoof 2015 dataset, evaluation, and results with detailed analyses. A review of post-evaluation studies conducted using the same dataset illustrates the rapid progress stemming from ASVspoof and outlines the need for further investigation. Priority future research directions are presented in the scope of the next ASVspoof evaluation planned for 2017.
ASVspoof 2015: the first automatic speaker verification spoofing and countermeasures challenge
2015
An increasing number of independent studies have confirmed the vulnerability of automatic speaker verification (ASV) technology to spoofing. However, in comparison to that involving other biometric modalities, spoofing and countermeasure research for ASV is still in its infancy. A current barrier to progress is the lack of standards which impedes the comparison of results generated by different researchers. The ASVspoof initiative aims to overcome this bottleneck through the provision of standard corpora, protocols and metrics to support a common evaluation. This paper introduces the first edition, summaries the results and discusses directions for future challenges and research.
On the vulnerability of speaker verification to realistic voice spoofing
2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS), 2015
Automatic speaker verification (ASV) systems are subject to various kinds of malicious attacks. Replay, voice conversion and speech synthesis attacks drastically degrade the performance of a standard ASV system by increasing its false acceptance rates. This issue raised a high level of interest in the speech research community where the possible voice spoofing attacks and their related countermeasures have been investigated. However, much less effort has been devoted in creating realistic and diverse spoofing attack databases that foster researchers to correctly evaluate their countermeasures against attacks. The existing studies are not complete in terms of types of attacks, and often difficult to reproduce because of unavailability of public databases. In this paper we introduce the voice spoofing data-set of AVspoof, a public audio-visual spoofing database. AVspoof includes ten realistic spoofing threats generated using replay, speech synthesis and voice conversion. In addition, we provide a set of experimental results that show the effect of such attacks on current state-of-the-art ASV systems.
2015
Automatic speaker verification (ASV) offers a low-cost and flexible biometric solution to person authentication. While the reliability of ASV systems is now considered sufficient to support mass-market adoption, there are concerns that the technology is vulnerable to spoofing, also referred to as presentation attacks. Spoofing refers to an attack whereby a fraudster attempts to manipulate a biometric system by masquerading as another, enrolled person. On the other hand, speaker adaptation in speech synthesis and voice conversion techniques attempt to mimic a target speaker’s voice automatically, and hence present a genuine threat to ASV systems. The research community has responded to speech synthesis and voice conversion spoofing attacks 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; ASV systems remain vulnerable to spoofing, and a deeper understanding of spe...
Multimedia Tools and Applications
The emergence of biometric technology provides enhanced security compared to the traditional identification and authentication techniques that were less efficient and secure. Despite the advantages brought by biometric technology, the existing biometric systems such as Automatic Speaker Verification (ASV) systems are weak against presentation attacks. A presentation attack is a spoofing attack launched to subvert an ASV system to gain access to the system. Though numerous Presentation Attack Detection (PAD) systems were reported in the literature, a systematic survey that describes the current state of research and application is unavailable. This paper presents a systematic analysis of the state-of-the-art voice PAD systems to promote further advancement in this area. The objectives of this paper are two folds: (i) to understand the nature of recent work on PAD systems, and (ii) to identify areas that require additional research. From the survey, a taxonomy of voice PAD and the tre...
Spoofing and countermeasures for automatic speaker verification
It is widely acknowledged that most biometric systems are vulnerable to spoofing, also known as imposture. While vulnerabilities and countermeasures for other biometric modalities have been widely studied, e.g. face verification, speaker verification systems remain vulnerable. This paper describes some specific vulnerabilities studied in the literature and presents a brief survey of recent work to develop spoofing countermeasures. The paper concludes with a discussion on the need for standard datasets, metrics and formal evaluations which are needed to assess vulnerabilities to spoofing in realistic scenarios without prior knowledge.
Re-assessing the threat of replay spoofing attacks against automatic speaker verification
This paper reexamines the threat of spoofing or presentation attacks in the context of automatic speaker verification (ASV). While voice conversion and speech synthesis attacks present as erious threat, and have accordingly receivedag reat deal of attention in the recent literature, theyc an only be implemented with ah igh level of technical know-how. In contrast, the implementation of replay attacks require no specific expertise nor anys ophisticated equipment and thus theya rguably present a greater risk. The comparative threat of each attack is reexamined in this paper against six different ASV systems including astate-of-the-art iVector-PLDAsystem. Despite the lack of attention in the literature, experiments showthat low-effort replay attacks provoke higher levels of false acceptance than comparatively higher-effort spoofing attacks such as voice conversion and speech synthesis. Results therefore showt he need to refocus research effort and to develop countermeasures against replay attacks in future work. * The work of A. Janicki wassupported by the European Union in the framework of the European Social Fund through the WarsawUniversity of Technology Development Programme.
An assessment of automatic speaker verification vulnerabilities to replay spoofing attacks
Security and Communication Networks, 2016
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.
2013
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.