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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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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. |
format | Online Article Text |
id | pubmed-5987295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
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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