Multimodal biometric user authentication using improved decentralized fuzzy vault scheme based on Blockchain network

Abstract

Biometric security has emerged as a major concern in the field of Biometric Systems. The existing centralized Biometric Cryptosystems approach still suffers from privacy issues and network-based attacks. In particular, the Biometric Cryptosystems are susceptible to Attack via Record Multiplicity, brute force and collusion attacks. To address these issues, this paper proposes a multimodal biometric user authentication scheme using a decentralized fuzzy vault based on Blockchain technology. In this scheme, the facial biometric images and dorsal hand images together form the multimodal biometric. The proposed security framework is implemented in two phases. In the first phase, multimodal biometric user authentication using an improved fuzzy vault scheme is implemented. In the second phase, a privacy preservation technique using a decentralized fuzzy vault biometric system based on the Blockchain network is implemented. The performance of the proposed framework is verified on the biometric datasets consisting of both genuine and imposter users, and a comparative analysis with the existing state-of-the-art approaches is also presented. The Detection Error Trade-off (DET) curve and the Receiver Operating Characteristic (ROC) curve, obtained for verifying the efficacy of the proposed framework, are also presented. The proposed framework yielded an accuracy of 99.8% and an Equal Error Rate of 0.08. Furthermore, to validate the biometric template protection, the security analysis of the proposed scheme based on irreversibility, unlinkability, and revocability criteria is described. The proposed framework achieves significant improvement in terms of a low False Acceptance Rate (0.08), and a high True Acceptance Rate (0.96).