Steganalysis of Audio Based on Audio Quality Metrics

Hamza Özer; Ismail Avcibaş; Bülent Sankur; Nasir Memon

doi:10.1117/12.477313

Steganalysis of Audio Based on Audio Quality Metrics

Hamza Özer, Ismail Avcibaş, Bülent Sankur, Nasir Memon

Center for Cyber Security

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Classification of audio documents as bearing hidden information or not is a security issue addressed in the context of steganalysis. A cover audio object can be converted into a stego-audio object via steganographic methods. In this study we present a statistical method to detect the presence of hidden messages in audio signals. The basic idea is that, the distribution of various statistical distance measures, calculated on cover audio signals and on stego-audio signals vis-à-vis their denoised versions, are statistically different. The design of audio steganalyzer relies on the choice of these audio quality measures and the construction of a two-class classifier. Experimental results show that the proposed technique can be used to detect the presence of hidden messages in digital audio data.

Original language	English (US)
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Editors	E.J. Delp III, P. Wah Wong
Pages	55-66
Number of pages	12
Volume	5020
DOIs	https://doi.org/10.1117/12.477313
State	Published - 2003
Event	Security and Watermarking of Multimedia Contents V - Santa Clara, CA, United States Duration: Jan 21 2003 → Jan 24 2003

Other

Other	Security and Watermarking of Multimedia Contents V
Country/Territory	United States
City	Santa Clara, CA
Period	1/21/03 → 1/24/03

Keywords

Audio quality measures
Feature selection
Steganalysis
Support vector machine
Watermarking

ASJC Scopus subject areas

Electrical and Electronic Engineering
Condensed Matter Physics

Access to Document

10.1117/12.477313

Cite this

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title = "Steganalysis of Audio Based on Audio Quality Metrics",

abstract = "Classification of audio documents as bearing hidden information or not is a security issue addressed in the context of steganalysis. A cover audio object can be converted into a stego-audio object via steganographic methods. In this study we present a statistical method to detect the presence of hidden messages in audio signals. The basic idea is that, the distribution of various statistical distance measures, calculated on cover audio signals and on stego-audio signals vis-{\`a}-vis their denoised versions, are statistically different. The design of audio steganalyzer relies on the choice of these audio quality measures and the construction of a two-class classifier. Experimental results show that the proposed technique can be used to detect the presence of hidden messages in digital audio data.",

keywords = "Audio quality measures, Feature selection, Steganalysis, Support vector machine, Watermarking",

author = "Hamza {\"O}zer and Ismail Avciba{\c s} and B{\"u}lent Sankur and Nasir Memon",

year = "2003",

doi = "10.1117/12.477313",

language = "English (US)",

volume = "5020",

pages = "55--66",

editor = "{Delp III}, E.J. and {Wah Wong}, P.",

booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

note = "Security and Watermarking of Multimedia Contents V ; Conference date: 21-01-2003 Through 24-01-2003",

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TY - GEN

T1 - Steganalysis of Audio Based on Audio Quality Metrics

AU - Özer, Hamza

AU - Avcibaş, Ismail

AU - Sankur, Bülent

AU - Memon, Nasir

PY - 2003

Y1 - 2003

N2 - Classification of audio documents as bearing hidden information or not is a security issue addressed in the context of steganalysis. A cover audio object can be converted into a stego-audio object via steganographic methods. In this study we present a statistical method to detect the presence of hidden messages in audio signals. The basic idea is that, the distribution of various statistical distance measures, calculated on cover audio signals and on stego-audio signals vis-à-vis their denoised versions, are statistically different. The design of audio steganalyzer relies on the choice of these audio quality measures and the construction of a two-class classifier. Experimental results show that the proposed technique can be used to detect the presence of hidden messages in digital audio data.

AB - Classification of audio documents as bearing hidden information or not is a security issue addressed in the context of steganalysis. A cover audio object can be converted into a stego-audio object via steganographic methods. In this study we present a statistical method to detect the presence of hidden messages in audio signals. The basic idea is that, the distribution of various statistical distance measures, calculated on cover audio signals and on stego-audio signals vis-à-vis their denoised versions, are statistically different. The design of audio steganalyzer relies on the choice of these audio quality measures and the construction of a two-class classifier. Experimental results show that the proposed technique can be used to detect the presence of hidden messages in digital audio data.

KW - Audio quality measures

KW - Feature selection

KW - Steganalysis

KW - Support vector machine

KW - Watermarking

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DO - 10.1117/12.477313

M3 - Conference contribution

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VL - 5020

SP - 55

EP - 66

BT - Proceedings of SPIE - The International Society for Optical Engineering

A2 - Delp III, E.J.

A2 - Wah Wong, P.

T2 - Security and Watermarking of Multimedia Contents V

Y2 - 21 January 2003 through 24 January 2003

ER -

Steganalysis of Audio Based on Audio Quality Metrics

Abstract

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Keywords

ASJC Scopus subject areas

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