Cancelable Voiceprint Template Based on Chaff-Points-Mixture Method

Xu, Wanhai; Cheng, Minying

doi:10.1109/cis.2008.49

Cited by 15 publications

(8 citation statements)

References 11 publications

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“…The use of template Protection methods for voice can be found in two studies by the same authors [12,13]. Both are classified as biometric cryptosystems, since the original voice data is recovered in order to be used in the authentication systems.…”

Section: Recent Studies In Cancellable Biometricsmentioning

confidence: 99%

“…In the second work [12], a method based on chaff points has been proposed. In the proposed method, firstly, the MFCC (Mel-Frequency Cepstrum Coeffecents) feature matrix and stochastic matrix are expanded by inserting zero rows.…”

Section: Recent Studies In Cancellable Biometricsmentioning

confidence: 99%

“…Several studies have been reported in the literature that apply template protection methods in several biometric modalities, such as face [5][6][7], fingerprint [8,9], signature [10,11] and voice [12,13], among others.…”

Section: Recent Studies In Cancellable Biometricsmentioning

confidence: 99%

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An effective template protection method for face and voice cancellable identification

Canuto¹,

Pintro²,

Fairhurst

2014

HIS

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Cancellable biometrics adopt an approach in which biometric templates can be cancelled and replaced if compromised, for example if they are lost or stolen, and can therefore overcome some of the security concerns about biometric-based authentication systems. This paper proposes a simple and effective template protection method (cancellable transformation) for providing cancellable data, called the double sum (DS) method, which performs a sum procedure over the attributes that makes the definition of the original data a hard (and almost impossible) process. In order to investigate the feasibility of the proposed method, an empirical analysis is conducted and we use as examples two different biometric modalities (face and voice) separately and in a multi-modal context (multi-biometric). The main aim of this paper is to provide greater security and improved performance in the biometric authentication process. The datasets used in this analysis were TIMIT for voice and the AR Face dataset for face. As a result of this analysis, we will observe that the proposed transformation offered higher performance to two existing cancellable transformations.

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Section: Recent Studies In Cancellable Biometricsmentioning

confidence: 99%

Section: Recent Studies In Cancellable Biometricsmentioning

confidence: 99%

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An effective template protection method for face and voice cancellable identification

Canuto¹,

Pintro²,

Fairhurst

2014

HIS

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“…Based on the fuzzy vault scheme [11], Xu et al [12] proposed a cancellable voice template protection. Chaff points are added to the Mel Frequency Cepstral Coefficient-MFCC matrix to compose a vault and to make hard for an adversary the separation of genuine points from the MFCC.…”

Section: Related Workmentioning

confidence: 99%

Cancelable speaker verification system based on binary Gaussian mixtures

Mtibaa

Petrovska‐Delacrétaz

Hamida

2018

2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

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Biometric systems suffer from non-revocabilty. In this paper, we propose a cancelable speaker verification system based on classical Gaussian Mixture Models (GMM) methodology enriched with the desired characteristics of revocability and privacy. The GMM model is transformed into a binary vector that is used by a shuffling scheme to generate a cancelable template and to guarantee the cancelabilty of the overall system. Leveraging the shuffling scheme, the speaker model can be revoked and another model can be reissued. Our proposed method enables the generation of multiple cancelable speaker templates from the same biometric modality that cannot be linked to the same user. The proposed system is evaluated on the RSR2015 databases. It outperforms the basic GMM system and experimentations show significant improvement in the speaker verification performance that achieves an Equal Error Rate (ERR) of 0.01%.

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“…Another cancelable biometric system was introduced in [5], which depend on a fuzzy vault scheme. A biometric protection based on adding chaff points to the Mel frequency Cepstral coefficient (MFCC) vector to align difficult for attackers to separate of actual points from MFCC was suggested in [6]. Although, the authentication at the receiver has complexity with separating the chaff points and has not able to compare between templates in transform domain.…”

Section: Introductionmentioning

confidence: 99%