research-article

Derivative-based audio steganalysis

Authors:

Andrew H. Sung,

Mengyu QiaoAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), Volume 7, Issue 3

Article No.: 18, Pages 1 - 19

https://doi.org/10.1145/2000486.2000492

Published: 02 September 2011 Publication History

Abstract

This article presents a second-order derivative-based audio steganalysis. First, Mel-cepstrum coefficients and Markov transition features from the second-order derivative of the audio signal are extracted; a support vector machine is then applied to the features for discovering the existence of hidden data in digital audio streams. Also, the relation between audio signal complexity and steganography detection accuracy, which is an issue relevant to audio steganalysis performance evaluation but so far has not been explored, is analyzed experimentally. Results demonstrate that, in comparison with a recently proposed signal stream-based Mel-cepstrum method, the second-order derivative-based audio steganalysis method gains a considerable advantage under all categories of signal complexity--especially for audio streams with high signal complexity, which are generally the most challenging for steganalysis-and thereby significantly improves the state of the art in audio steganalysis.

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Cited By

Lewandowski M(2024)Estimating the first and second derivatives of discrete audio dataEURASIP Journal on Audio, Speech, and Music Processing10.1186/s13636-024-00355-52024:1Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1186/s13636-024-00355-5
Su WNi JHu XLi B(2024)Efficient Audio Steganography Using Generalized Audio Intrinsic Energy With Micro-Amplitude Modification SuppressionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.341726819(6559-6572)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3417268
Zhang XChen KDing JYang YZhang WYu N(2024)Provably Secure Public-Key Steganography Based on Elliptic Curve CryptographyIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.336121919(3148-3163)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3361219
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Index Terms

Derivative-based audio steganalysis

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Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 7, Issue 3

August 2011

117 pages

ISSN:1551-6857

EISSN:1551-6865

DOI:10.1145/2000486

Issue’s Table of Contents

Copyright © 2011 ACM.

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Association for Computing Machinery

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Publication History

Published: 02 September 2011

Accepted: 01 May 2010

Revised: 01 April 2010

Received: 01 August 2008

Published in TOMM Volume 7, Issue 3

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Cited By

Lewandowski M(2024)Estimating the first and second derivatives of discrete audio dataEURASIP Journal on Audio, Speech, and Music Processing10.1186/s13636-024-00355-52024:1Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1186/s13636-024-00355-5
Su WNi JHu XLi B(2024)Efficient Audio Steganography Using Generalized Audio Intrinsic Energy With Micro-Amplitude Modification SuppressionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.341726819(6559-6572)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3417268
Zhang XChen KDing JYang YZhang WYu N(2024)Provably Secure Public-Key Steganography Based on Elliptic Curve CryptographyIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.336121919(3148-3163)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3361219
Chen HZhang JChen KZhang WYu N(2024)Model Access Control Based on Hidden Adversarial Examples for Automatic Speech RecognitionIEEE Transactions on Artificial Intelligence10.1109/TAI.2023.32858585:3(1302-1315)Online publication date: Mar-2024
https://doi.org/10.1109/TAI.2023.3285858
Li JHe PLiu JLuo JXia Q(2023)Cover Enhancement Method for Audio Steganography Based on Universal Adversarial Perturbations with Sample DiversificationComputers, Materials & Continua10.32604/cmc.2023.03681975:3(4893-4915)Online publication date: 2023
https://doi.org/10.32604/cmc.2023.036819
Peng FJiang WLong M(2023)A Low Distortion and Steganalysis-resistant Reversible Data Hiding for 2D Engineering GraphicsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/353966119:2(1-20)Online publication date: 6-Feb-2023
https://dl.acm.org/doi/10.1145/3539661
Kosch TWelsch RChuang LSchmidt A(2023)The Placebo Effect of Artificial Intelligence in Human–Computer InteractionACM Transactions on Computer-Human Interaction10.1145/352922529:6(1-32)Online publication date: 11-Jan-2023
https://dl.acm.org/doi/10.1145/3529225
Greenhalgh CHazzard ABenford SCliffe LKelly E(2022)Crafting Trajectories of Smart Phone Use at the OperaACM Transactions on Computer-Human Interaction10.1145/353100729:6(1-37)Online publication date: 16-Nov-2022
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Yang ZYang HChang CHuang YChang C(2022)Real-time steganalysis for streaming media based on multi-channel convolutional sliding windowsKnowledge-Based Systems10.1016/j.knosys.2021.107561237:COnline publication date: 15-Feb-2022
https://dl.acm.org/doi/10.1016/j.knosys.2021.107561
Lin YWang RDong LYan DWang J(2021)Tackling the Cover Source Mismatch Problem in Audio Steganalysis With Unsupervised Domain AdaptationIEEE Signal Processing Letters10.1109/LSP.2020.302223728(1475-1479)Online publication date: 2021
https://doi.org/10.1109/LSP.2020.3022237
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