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A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System
In this paper, a framework for authorization and personal image protection that applies user accounts, passwords, and personal I-vectors as the keys for ciphering the image content was developed and connected. There were two main systems in this framework. The first involved a speaker verification s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10347242/ https://www.ncbi.nlm.nih.gov/pubmed/37447756 http://dx.doi.org/10.3390/s23135906 |
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author | Li, Shih-Yu Lee, Chun-Hung Tam, Lap-Mou |
author_facet | Li, Shih-Yu Lee, Chun-Hung Tam, Lap-Mou |
author_sort | Li, Shih-Yu |
collection | PubMed |
description | In this paper, a framework for authorization and personal image protection that applies user accounts, passwords, and personal I-vectors as the keys for ciphering the image content was developed and connected. There were two main systems in this framework. The first involved a speaker verification system, wherein the user entered their account information and password to log into the system and provided a short voice sample for identification, and then the algorithm transferred the user’s voice (biometric) features, along with their account and password details, to a second image encryption system. For the image encryption process, the account name and password presented by the user were applied to produce the initial conditions for hyper-chaotic systems to generate private keys for image-shuffling and ciphering. In the final stage, the biometric features were also applied to protect the content of the image, so the encryption technology would be more robust. The final results of the encryption system were acceptable, as a lower correlation was obtained in the cipher images. The voice database we applied was the Pitch Tracking Database from the Graz University of Technology (PTDB-TUG), which provided the microphone and laryngoscope signals of 20 native English speakers. For image processing, four standard testing images from the University of Southern California–Signal and Image Processing Institute (USC-SIPI), including Lena, F-16, Mandrill, and Peppers, were presented to further demonstrate the effectiveness and efficiency of the smart image encryption algorithm. |
format | Online Article Text |
id | pubmed-10347242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103472422023-07-15 A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System Li, Shih-Yu Lee, Chun-Hung Tam, Lap-Mou Sensors (Basel) Article In this paper, a framework for authorization and personal image protection that applies user accounts, passwords, and personal I-vectors as the keys for ciphering the image content was developed and connected. There were two main systems in this framework. The first involved a speaker verification system, wherein the user entered their account information and password to log into the system and provided a short voice sample for identification, and then the algorithm transferred the user’s voice (biometric) features, along with their account and password details, to a second image encryption system. For the image encryption process, the account name and password presented by the user were applied to produce the initial conditions for hyper-chaotic systems to generate private keys for image-shuffling and ciphering. In the final stage, the biometric features were also applied to protect the content of the image, so the encryption technology would be more robust. The final results of the encryption system were acceptable, as a lower correlation was obtained in the cipher images. The voice database we applied was the Pitch Tracking Database from the Graz University of Technology (PTDB-TUG), which provided the microphone and laryngoscope signals of 20 native English speakers. For image processing, four standard testing images from the University of Southern California–Signal and Image Processing Institute (USC-SIPI), including Lena, F-16, Mandrill, and Peppers, were presented to further demonstrate the effectiveness and efficiency of the smart image encryption algorithm. MDPI 2023-06-26 /pmc/articles/PMC10347242/ /pubmed/37447756 http://dx.doi.org/10.3390/s23135906 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Shih-Yu Lee, Chun-Hung Tam, Lap-Mou A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System |
title | A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System |
title_full | A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System |
title_fullStr | A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System |
title_full_unstemmed | A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System |
title_short | A Smart Image Encryption Technology via Applying Personal Information and Speaker-Verification System |
title_sort | smart image encryption technology via applying personal information and speaker-verification system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10347242/ https://www.ncbi.nlm.nih.gov/pubmed/37447756 http://dx.doi.org/10.3390/s23135906 |
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