Perceptual Digest Function for Verifying Integrity in Audio Forensics

In this work we propose a function that allows to calculate a summary code from the parameters of a voice signal. This function is based on ordering of spectral coefficients obtained by means of the application of the Fast Fourier Transform (FFT), using a locally generated reference function (Gaussi...

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Authors: Ballesteros L., Dora M., Renza, Diego, Ortiz, Héctor Duvan
Format: article
Status:Published version
Publication Date:2017
Country:Colombia
Institution:Universidad EAFIT
Repository:Repositorio EAFIT
Language:Spanish
OAI Identifier:oai:repository.eafit.edu.co:10784/13175
Online Access:http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/4624
http://hdl.handle.net/10784/13175
Access Level:Open access
Keyword:Hash function
Perceptual hash
Integrity
Audio forensics
Función resumen
Función perceptual
Integridad
Audio forense
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spelling Perceptual Digest Function for Verifying Integrity in Audio ForensicsFunción resumen perceptual para verificación de integridad en audio forenseBallesteros L., Dora M.Renza, DiegoOrtiz, Héctor DuvanHash functionPerceptual hashIntegrityAudio forensicsFunción resumenFunción perceptualIntegridadAudio forenseIn this work we propose a function that allows to calculate a summary code from the parameters of a voice signal. This function is based on ordering of spectral coefficients obtained by means of the application of the Fast Fourier Transform (FFT), using a locally generated reference function (Gaussian random noise). The proposed method is oriented to the verification of integrity in forensic voice signals. The proposed methodology has a perceptual approach, which implies that the resulting code is maintained, even when modifications are made, particularly those that do not affect the sensitive content of the signal, such as re-quantization processes.En este artículos se propone una función que permite calcular un código resumen a partir de los parámetros de una señal de voz. Esta función está basada en el ordenamiento de los coeficientes espectrales en un proceso de imitación entre el espectro de la señal de voz y el espectro de una señal de ruido gaussiano generada localmente. El método de función resumen está orientado a la verificación de integridad forense en señales de voz, con un enfoque perceptual, que implica que la función resumen no cambia si la señal sufre modificaciones que no alteran el contenido (como re-cuantización), pero que si cambia ante modificaciones como recorte y adición de ruido. Se realizaron diversas pruebas para verificar el enfoque perceptual del método resumen propuesto y se compararon los resultados frente a modificaciones utilizando métodos tradicionales.Universidad EAFITUniversidad Militar Nueva Granada2017-05-022018-11-16T16:28:57Z2017-05-022018-11-16T16:28:57Zinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionarticlepublishedVersionArtículoapplication/pdfapplication/pdftext/html2256-43141794-9165http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/4624http://hdl.handle.net/10784/1317510.17230/ingciencia.13.25.7Ingeniería y Ciencia; Vol 13 No 25 (2017); 167-183Ingeniería y Ciencia; Vol 13 No 25 (2017); 167-183reponame:Repositorio EAFITinstname:Universidad EAFITinstacron:Universidad EAFITspahttp://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/4624Copyright (c) 2017 Dora M. Ballesteros L.; Diego Renza, Héctor Duvan OrtizAttribution 4.0 International (CC BY 4.0)http://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessAcceso abierto2020-03-01T22:44:27Z
dc.title.none.fl_str_mv Perceptual Digest Function for Verifying Integrity in Audio Forensics
Función resumen perceptual para verificación de integridad en audio forense
title Perceptual Digest Function for Verifying Integrity in Audio Forensics
spellingShingle Perceptual Digest Function for Verifying Integrity in Audio Forensics
Ballesteros L., Dora M.
Hash function
Perceptual hash
Integrity
Audio forensics
Función resumen
Función perceptual
Integridad
Audio forense
title_short Perceptual Digest Function for Verifying Integrity in Audio Forensics
title_full Perceptual Digest Function for Verifying Integrity in Audio Forensics
title_fullStr Perceptual Digest Function for Verifying Integrity in Audio Forensics
title_full_unstemmed Perceptual Digest Function for Verifying Integrity in Audio Forensics
title_sort Perceptual Digest Function for Verifying Integrity in Audio Forensics
dc.creator.none.fl_str_mv Ballesteros L., Dora M.
Renza, Diego
Ortiz, Héctor Duvan
author Ballesteros L., Dora M.
author_facet Ballesteros L., Dora M.
Renza, Diego
Ortiz, Héctor Duvan
author_role author
author2 Renza, Diego
Ortiz, Héctor Duvan
author2_role author
author
dc.contributor.none.fl_str_mv Universidad Militar Nueva Granada
dc.subject.none.fl_str_mv Hash function
Perceptual hash
Integrity
Audio forensics
Función resumen
Función perceptual
Integridad
Audio forense
topic Hash function
Perceptual hash
Integrity
Audio forensics
Función resumen
Función perceptual
Integridad
Audio forense
description In this work we propose a function that allows to calculate a summary code from the parameters of a voice signal. This function is based on ordering of spectral coefficients obtained by means of the application of the Fast Fourier Transform (FFT), using a locally generated reference function (Gaussian random noise). The proposed method is oriented to the verification of integrity in forensic voice signals. The proposed methodology has a perceptual approach, which implies that the resulting code is maintained, even when modifications are made, particularly those that do not affect the sensitive content of the signal, such as re-quantization processes.
publishDate 2017
dc.date.none.fl_str_mv 2017-05-02
2017-05-02
2018-11-16T16:28:57Z
2018-11-16T16:28:57Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
article
publishedVersion
Artículo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 2256-4314
1794-9165
http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/4624
http://hdl.handle.net/10784/13175
10.17230/ingciencia.13.25.7
identifier_str_mv 2256-4314
1794-9165
10.17230/ingciencia.13.25.7
url http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/4624
http://hdl.handle.net/10784/13175
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv http://publicaciones.eafit.edu.co/index.php/ingciencia/article/view/4624
dc.rights.none.fl_str_mv Copyright (c) 2017 Dora M. Ballesteros L.; Diego Renza, Héctor Duvan Ortiz
Attribution 4.0 International (CC BY 4.0)
http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
Acceso abierto
rights_invalid_str_mv Copyright (c) 2017 Dora M. Ballesteros L.; Diego Renza, Héctor Duvan Ortiz
Attribution 4.0 International (CC BY 4.0)
http://creativecommons.org/licenses/by/4.0
Acceso abierto
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
text/html
dc.publisher.none.fl_str_mv Universidad EAFIT
publisher.none.fl_str_mv Universidad EAFIT
dc.source.none.fl_str_mv Ingeniería y Ciencia; Vol 13 No 25 (2017); 167-183
Ingeniería y Ciencia; Vol 13 No 25 (2017); 167-183
reponame:Repositorio EAFIT
instname:Universidad EAFIT
instacron:Universidad EAFIT
instname_str Universidad EAFIT
instacron_str Universidad EAFIT
institution Universidad EAFIT
reponame_str Repositorio EAFIT
collection Repositorio EAFIT
_version_ 1825051048888238080
score 15.812455

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