Faculty Publications
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Publications by NITK Faculty
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Item A Novel Cancelable Fingerprint Template Generation Mechanism Using Visual Secret Sharing(Springer Science and Business Media Deutschland GmbH, 2024) Muhammed, A.; Pais, A.R.In fingerprint-based authentication system, cancelable fingerprint templates are generated to defend the fingerprint information. In this paper, we proposed a novel cancelable fingerprint template using Visual Secret Sharing (VSS). Using VSS, each fingerprint image is encrypted into different shares. Finally, these shares are preserved in distinct databases and treated as fingerprint template. Traditional VSS schemes are suffering from pixel expansion and contrast reduction. We have used grid-based VSS and data embedding mechanisms to succeed these limitations. The proposed fingerprint templates satisfy ideal properties of cancelable templates such as non-invertibility, diversity, and revocability without altering the performance of the authentication system. To enhance the speed of the template generation and reconstruction, we have used General Purpose Graphical Processing Unit (GPGPU) to fulfill the operations. The experimental evaluation validates that the reconstructed fingerprints have equivalent performance as the initial fingerprints with upgraded security. © Springer Nature Switzerland AG 2024.Item A novel fingerprint template protection and fingerprint authentication scheme using visual secret sharing and super-resolution(Springer, 2021) Muhammed, A.; Mhala, N.C.; Pais, A.R.Fingerprint is the most recommended and extensively practicing biometric trait for personal authentication. Most of the fingerprint authentication systems trust minutiae as the characteristic for authentication. These characteristics are preserved as fingerprint templates in the database. However, it is observed that the databases are not secure and can be negotiated. Recent studies reveal that, if a person’s minutiae points are dripped, fingerprint can be restored from these points. Similarly, if the fingerprint records are lost, it is a permanent damage. There is no mechanism to replace the fingerprint as it is part of the human body. Hence there is a necessity to secure the fingerprint template in the database. In this paper, we introduce a novel fingerprint template protection and fingerprint authentication scheme using visual secret sharing and super-resolution. During enrollment, a secret fingerprint image is encrypted into n shares. Each share is stored in a distinct database. During authentication, the shares are collected from various databases. The original secret fingerprint image is restored using a multiple image super-resolution procedure. The experimental results show that the reconstructed fingerprints are similar to the original fingerprints. The proposed method is robust, secure, and efficient in terms of fingerprint template protection and authentication. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.Item A secure fingerprint template generation mechanism using visual secret sharing with inverse halftoning(Academic Press Inc., 2023) Muhammed, A.; Pais, A.R.Fingerprints are the most popular and widely practiced biometric trait for human recognition and authentication. Due to the wide approval, reliable fingerprint template generation and secure saving of the generated templates are highly vital. Since fingers are permanently connected to the human body, loss of fingerprint data is irreversible. Cancelable fingerprint templates are used to overcome this problem. This paper introduces a novel cancelable fingerprint template generation mechanism using Visual Secret Sharing (VSS), data embedding, inverse halftoning, and super-resolution. During the fingerprint template generation, VSS shares with some hidden information are formulated as the secure cancelable template. Before authentication, the secret fingerprint image is reconstructed back from the VSS shares. The experimental results show that the proposed cancelable templates are simple, secure, and fulfill all the properties of the ideal cancelable templates, such as security, accuracy, non-invertibility, diversity, and revocability. The experimental analysis shows that the reconstructed fingerprint images are similar to the original fingerprints in terms of visual parameters and matching error rates. © 2023 Elsevier Inc.