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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...

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Detalles Bibliográficos
Autores principales: Renza, Diego, Mendoza, Sebastian, Ballesteros L, Dora M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
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.
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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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