http://cs.uef.fi/sipu/pub/SRE-review-Kinnunen-and-Li.pdf

An overview of text-independent speaker recognition: From features to supervectors

Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.

/pdf/biometric-template-security-3nxd1k841h.pdf

Biometric template security

This survey aims at providing multimedia researchers with a state-of-the-art overview of fusion strategies, which are used for combining multiple modalities in order to accomplish various multimedia analysis tasks. The existing literature on multimodal fusion research is presented through several classifications based on the fusion methodology and the level of fusion (feature, decision, and hybrid). The fusion methods are described from the perspective of the basic concept, advantages, weaknesses, and their usage in various analysis tasks as reported in the literature. Moreover, several distinctive issues that influence a multimodal fusion process such as, the use of correlation and independence, confidence level, contextual information, synchronization between different modalities, and the optimal modality selection are also highlighted. Finally, we present the open issues for further research in the area of multimodal fusion.

/pdf/multimodal-fusion-for-multimedia-analysis-a-survey-5f9wxprbby.pdf

Multimodal fusion for multimedia analysis: a survey

We investigate whether a classifier can continuously authenticate users based on the way they interact with the touchscreen of a smart phone. We propose a set of 30 behavioral touch features that can be extracted from raw touchscreen logs and demonstrate that different users populate distinct subspaces of this feature space. In a systematic experiment designed to test how this behavioral pattern exhibits consistency over time, we collected touch data from users interacting with a smart phone using basic navigation maneuvers, i.e., up-down and left-right scrolling. We propose a classification framework that learns the touch behavior of a user during an enrollment phase and is able to accept or reject the current user by monitoring interaction with the touch screen. The classifier achieves a median equal error rate of 0% for intrasession authentication, 2%-3% for intersession authentication, and below 4% when the authentication test was carried out one week after the enrollment phase. While our experimental findings disqualify this method as a standalone authentication mechanism for long-term authentication, it could be implemented as a means to extend screen-lock time or as a part of a multimodal biometric authentication system.

/pdf/touchalytics-on-the-applicability-of-touchscreen-input-as-a-3a6lvvm3fr.pdf

Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication

In recent years, along with the extraordinary diffusion of the Internet and a growing need for personal verification in many daily applications, automatic signature verification is being considered with renewed interest. This paper presents the state of the art in automatic signature verification. It addresses the most valuable results obtained so far and highlights the most profitable directions of research to date. It includes a comprehensive bibliography of more than 300 selected references as an aid for researchers working in the field.

/pdf/automatic-signature-verification-the-state-of-the-art-68njryqnhw.pdf

Automatic Signature Verification: The State of the Art

This paper is focused on algorithmic issues for biometric face verification (i.e., given an image of the face and an identity claim, decide whether they correspond to each other or not). Several alternatives for geometric normalization of images, photometric normalization, dimensionality reduction and similarity measures are proposed and compared using the XM2VTS database and the associated Lausanne protocol [K. Messer et al., 1999], [J. Luettin et al., 1998]. Experiments under this particular framework show that best verification results are obtained when holistic approaches for face recognition (such as eigenfaces or fisherfaces) are combined with techniques traditionally associated to local feature-based approaches, such as Gabor decompositions.

A comparative evaluation of global representation-based schemes for face verification

On the relation between biometric quality and user-dependent score distributions in fingerprint verification

/pdf/on-the-relation-between-biometric-quality-and-user-dependent-za3cz5o62v.pdf

Automatic speaker recognition systems have been largely dominated by acoustic-spectral-based systems, relying in proper modelling of the short-term vocal tract of speakers. However, there is scientific and intuitive evidence that speaker-specific information is embedded in the speech signal in multiple short- and long-term characteristics. In this work, a multilevel speaker recognition system combining acoustic, phonotactic, and prosodic subsystems is presented and assessed by blind submission to NIST 2005 Speaker Recognition Evaluation

J. Fierrez-Aguilar

Papers

A comparative evaluation of global representation-based schemes for face verification

On the relation between biometric quality and user-dependent score distributions in fingerprint verification

Speaker Recognition The A TVS-UAM System at NIST SRE 05