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Encrypted audio dataset based on the Collatz conjecture
In information security, one way to keep a secret content is through encryption. The objective is to alter the content so that it is not intelligible, and therefore only the intended user can reveal the secret content. With the aim to provide examples of encrypted audio data, we applied a novel meth...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811906/ https://www.ncbi.nlm.nih.gov/pubmed/31667298 http://dx.doi.org/10.1016/j.dib.2019.104537 |
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author | Renza, Diego Mendoza, Sebastian Ballesteros L, Dora M. |
author_facet | Renza, Diego Mendoza, Sebastian Ballesteros L, Dora M. |
author_sort | Renza, Diego |
collection | PubMed |
description | In information security, one way to keep a secret content is through encryption. The objective is to alter the content so that it is not intelligible, and therefore only the intended user can reveal the secret content. With the aim to provide examples of encrypted audio data, we applied a novel method of encryption based on the Collatz conjecture in five hundred speech recordings (50 speakers, 10 different messages), and then five hundred encrypted audio files were obtained. The main characteristics of our encrypted recordings are as follows: the spectrogram is quasi-uniform, histograms have a repetitive pattern, average of samples is around −0.4, standard deviation is around 0.55; Shannon entropy is around 7.5 (for 8-bits per sample). The novelty of the results consists in obtaining a completely different behavior than natural speech recordings, i.e.: spectrogram with higher energy in low frequencies, histogram with Gaussian behavior, average of samples around 0, standard deviation around 0.11, entropy around 5.5. A more comprehensive analysis of our encrypted signals may be obtained from the article “High-uncertainty audio signal encryption based on the Collatz conjecture” in the Journal of Information Security and Applications. |
format | Online Article Text |
id | pubmed-6811906 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68119062019-10-30 Encrypted audio dataset based on the Collatz conjecture Renza, Diego Mendoza, Sebastian Ballesteros L, Dora M. Data Brief Computer Science In information security, one way to keep a secret content is through encryption. The objective is to alter the content so that it is not intelligible, and therefore only the intended user can reveal the secret content. With the aim to provide examples of encrypted audio data, we applied a novel method of encryption based on the Collatz conjecture in five hundred speech recordings (50 speakers, 10 different messages), and then five hundred encrypted audio files were obtained. The main characteristics of our encrypted recordings are as follows: the spectrogram is quasi-uniform, histograms have a repetitive pattern, average of samples is around −0.4, standard deviation is around 0.55; Shannon entropy is around 7.5 (for 8-bits per sample). The novelty of the results consists in obtaining a completely different behavior than natural speech recordings, i.e.: spectrogram with higher energy in low frequencies, histogram with Gaussian behavior, average of samples around 0, standard deviation around 0.11, entropy around 5.5. A more comprehensive analysis of our encrypted signals may be obtained from the article “High-uncertainty audio signal encryption based on the Collatz conjecture” in the Journal of Information Security and Applications. Elsevier 2019-09-17 /pmc/articles/PMC6811906/ /pubmed/31667298 http://dx.doi.org/10.1016/j.dib.2019.104537 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Computer Science Renza, Diego Mendoza, Sebastian Ballesteros L, Dora M. Encrypted audio dataset based on the Collatz conjecture |
title | Encrypted audio dataset based on the Collatz conjecture |
title_full | Encrypted audio dataset based on the Collatz conjecture |
title_fullStr | Encrypted audio dataset based on the Collatz conjecture |
title_full_unstemmed | Encrypted audio dataset based on the Collatz conjecture |
title_short | Encrypted audio dataset based on the Collatz conjecture |
title_sort | encrypted audio dataset based on the collatz conjecture |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811906/ https://www.ncbi.nlm.nih.gov/pubmed/31667298 http://dx.doi.org/10.1016/j.dib.2019.104537 |
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