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A Novel Fingerprint Biometric Cryptosystem Based on Convolutional Neural Networks
dc.creator | Barzut, Srđan | |
dc.creator | Milosavljević, Milan | |
dc.creator | Adamović, Saša | |
dc.creator | Saračević, Muzafer | |
dc.creator | Maček, Nemanja | |
dc.creator | Gnjatović, Milan | |
dc.date.accessioned | 2023-12-05T10:31:50Z | |
dc.date.available | 2023-12-05T10:31:50Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 2227-7390 | |
dc.identifier.uri | http://jakov.kpu.edu.rs/handle/123456789/1511 | |
dc.description.abstract | Modern access controls employ biometrics as a means of authentication to a great extent. For example, biometrics is used as an authentication mechanism implemented on commercial devices such as smartphones and laptops. This paper presents a fingerprint biometric cryptosystem based on the fuzzy commitment scheme and convolutional neural networks. One of its main contributions is a novel approach to automatic discretization of fingerprint texture descriptors, entirely based on a convolutional neural network, and designed to generate fixed-length templates. By converting templates into the binary domain, we developed the biometric cryptosystem that can be used in key-release systems or as a template protection mechanism in fingerprint matching biometric systems. The problem of biometric data variability is marginalized by applying the secure block-level Bose– Chaudhuri–Hocquenghem error correction codes, resistant to statistical-based attacks. The evaluation shows significant performance gains when compared to other texture-based fingerprint matching and biometric cryptosystems. | sr |
dc.language.iso | en | sr |
dc.publisher | Basel, Switzerland : MDPI | sr |
dc.rights | ||
dc.rights | ||
dc.rights | restrictedAccess | sr |
dc.source | Mathematics | sr |
dc.subject | biometric cryptosystem | sr |
dc.subject | fuzzy commitment scheme | sr |
dc.subject | fingerprint recognition | sr |
dc.subject | machine learning | sr |
dc.subject | convolutional neural network | sr |
dc.title | A Novel Fingerprint Biometric Cryptosystem Based on Convolutional Neural Networks | sr |
dc.type | article | sr |
dc.rights.license | ARR | sr |
dc.citation.volume | 9 | |
dc.citation.issue | 7 | |
dc.citation.spage | 730 | |
dc.identifier.doi | 10.3390/math9070730 | |
dc.type.version | publishedVersion | sr |