Abstract

Multi-biometric system stores multiple templates for the same user corresponding to the different biometric sources. Infallible security should be provided to the stored biometric templates as biometric is not revocable. In this work, multi-modal biometric template security for palmprint and fingerprint is proposed which is based on the fuzzy vault generation. At first, the preprocessing steps are applied and subsequently, the features are extracted and combined. For recognition, we match the feature vectors of images. The multi-modal biometric template along with the input key are used to generate the fuzzy vault. In the decoding process, the template is given as input and is combined with the stored fuzzy vault to generate the corresponding final key. The experimentation is carried out using CASIA database for palmprint and FVC 2004 database for fingerprint. The evaluation metrics have FMR and FNMR value parameters.

Highlights

  • Biometric systems automatically determine or verify a person’s identity based on his anatomical and behavioral characteristics such as fingerprint, palmprint, vein pattern, finger knuckles, face, Iris, voice and gait

  • Stolen biometric templates can be used to compromise the security of the system in the following two ways: (i) The stolen template can be replayed to the matcher to gain unauthorized access, and (ii) a physical spoof can be created from the template [1] to gain unauthorized access to the system

  • We propose a unified scheme to secure multiple templates of a user in a multibiometric system by (i) transforming features from different biometric sources into a common representation, (ii) performing feature-level fusion to derive a single multibiometric template, and (iii) securing the multibiometric template using a single fuzzy vault construct

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Summary

Introduction

Biometric systems automatically determine or verify a person’s identity based on his anatomical and behavioral characteristics such as fingerprint, palmprint, vein pattern, finger knuckles, face, Iris, voice and gait. Unlike passwords, when biometric templates are compromised, it is not possible for a genuine user to revoke his biometric identifiers and switch to another set of uncompromised identifiers. Due to this irretrievable nature of biometric data, an attack against the stored templates constitutes a major security and privacy peril in a biometric system. A series of automated biometric-based identification methods have emerged which include fingerprint, palmprint, iris pattern, voice, etc. Palmprint images should be normalized and oriented before feature extraction It contains more information than fingerprints, so they are more distinctive. The computational complexity information about the ridges and other minutiae in the neighborhood of a minutia

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