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Combining Cryptography with EEG Biometrics

Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometric...

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Detalles Bibliográficos
Autores principales: Damaševičius, Robertas, Maskeliūnas, Rytis, Kazanavičius, Egidijus, Woźniak, Marcin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987295/
https://www.ncbi.nlm.nih.gov/pubmed/29951089
http://dx.doi.org/10.1155/2018/1867548
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author Damaševičius, Robertas
Maskeliūnas, Rytis
Kazanavičius, Egidijus
Woźniak, Marcin
author_facet Damaševičius, Robertas
Maskeliūnas, Rytis
Kazanavičius, Egidijus
Woźniak, Marcin
author_sort Damaševičius, Robertas
collection PubMed
description Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.
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spelling pubmed-59872952018-06-27 Combining Cryptography with EEG Biometrics Damaševičius, Robertas Maskeliūnas, Rytis Kazanavičius, Egidijus Woźniak, Marcin Comput Intell Neurosci Research Article Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024. Hindawi 2018-05-22 /pmc/articles/PMC5987295/ /pubmed/29951089 http://dx.doi.org/10.1155/2018/1867548 Text en Copyright © 2018 Robertas Damaševičius et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Damaševičius, Robertas
Maskeliūnas, Rytis
Kazanavičius, Egidijus
Woźniak, Marcin
Combining Cryptography with EEG Biometrics
title Combining Cryptography with EEG Biometrics
title_full Combining Cryptography with EEG Biometrics
title_fullStr Combining Cryptography with EEG Biometrics
title_full_unstemmed Combining Cryptography with EEG Biometrics
title_short Combining Cryptography with EEG Biometrics
title_sort combining cryptography with eeg biometrics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5987295/
https://www.ncbi.nlm.nih.gov/pubmed/29951089
http://dx.doi.org/10.1155/2018/1867548
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