article

A new adaptive digital audio watermarking based on support vector machine

Authors:

Xiang-Yang Wang,

Wei QiAuthors Info & Claims

Journal of Network and Computer Applications, Volume 31, Issue 4

Pages 735 - 749

https://doi.org/10.1016/j.jnca.2007.10.001

Published: 01 November 2008 Publication History

Abstract

It is a challenging work to design a robust digital audio watermarking scheme against desynchronization attacks. On the basis of support vector machines (SVMs), a new robust digital audio watermarking algorithm against desynchronization attacks is proposed in this paper, and in this the audio statistics characteristics and synchronization code are utilized. Firstly, the optimal embedding positions are located adaptively by using the SVM theory. Secondly, the 16-bit Barker code is chosen as synchronization mark and embedded into the digital audio by modifying the statistics average value of several samples. Finally, the digital watermark are embedded into the statistics average value of low-frequency components in wavelet domain by making full use of auditory masking. Experimental results show that the proposed scheme is inaudible and robust against common signal processing such as MP3 compression, low-pass filtering, noise addition, equalization, etc., and is robust against desynchronization attacks such as random cropping, amplitude variation, pitch shifting, time-scale modification, jittering, etc.

References

[1]

Barni M, Cox IJ, Kalker T. Digital watermarking. In: Fourth international workshop, international workshop on digital watermarking 2005 (IWDW 2005), Siena, Italy, September 15-17, 2005, Lecture notes in computer science, vol. 3710. Berlin: Springer; 2005. p. 260-74.

[2]

The first 50 years of electronic watermarking. J Appl Signal Process. v56 i2. 225-230.

[3]

An audio watermarking detecting improved algorithm based on HAS. J Eng Graphics. v26 i1. 74-79.

[4]

Girin L, Marchand S. Watermarking of speech signals using the sinusoidal model and frequency modulation of the partials. In: IEEE international conference on acoustics, speech, and signal processing (ICASSP 2004), 2004, p. 633-6.

[5]

Huang JW, Wang Y, Shi YQ. A blind audio watermarking algorithm with self-synchronization. In: Proceedings of the IEEE international symposium on circuits system, Arizona, USA, vol. 3, 2002. p. 627-30.

[6]

Kim HJ. Audio watermarking techniques. In: Pacific rim workshop on digital steganography, Kyushu Institute of Technology, Kitakyushu, Japan, July 3-4, 2003.

[7]

Spread spectrum watermarking of audio signals. IEEE Trans Signal Process. v51 i4. 1020-1033.

[8]

Audio watermarking through modification of tonal maskers. ETRI J. v27 i5. 608-661.

[9]

Li W, Xue XY. Audio watermarking based on music content analysis: robust against time scale modification. In: Proceedings of the second international workshop on digital watermarking, Korea, 2003a. p. 289-300.

[10]

An audio watermarking technique that is robust against random cropping. Comput Music J. v27 i4. 58-68.

[11]

A robust audio watermarking scheme based on MPEG 1 layer ß compression. In: Communications and multimedia security-CMS 2003. Lecture notes in computer science, vol. 963, Springer, New York. pp. 226-238.

[12]

A novel audio watermarking algorithm for copyright protection of digital audio. ETRI J. v24 i3. 181-189.

[13]

The nature of statistical learning theory. Springer, New York.

[14]

A novel synchronization invariant digital watermarking scheme based on DWT and DCT. IEEE Trans Signal Process. v54 i12. 4835-4840.

[15]

Overview of digital audio watermarking. J Commun. v26 i2. 100-111.

[16]

Wen-Nung L, Li-Chun C. Robust and high-quality time-domain audio watermarking subject to psycho acoustic masking. In: Proceedings of the IEEE international symposium on circuits systems, Arizona, USA, vol. 2, 2002. p. 45-8.

[17]

Wu C-P, Su P-C, Jay Kuo C-C. Robust audio watermarking for copyright protection. In: Conference on advanced signal processing: architectures, and implementations IX, SPIE's annual meeting, Denver, CO, vol. 3807, July 1999, p. 387-97.

[18]

Efficiently self-synchronized audio watermarking for assured audio data transmission. IEEE Trans Broadcast. v51 i1. 69-76.

Cited By

Khan AJabeen FNaz FSuhail SAhmed MNawaz S(2016)Buyer seller watermarking protocols issues and challenges A surveyJournal of Network and Computer Applications10.1016/j.jnca.2016.08.02675:C(317-334)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.jnca.2016.08.026
Latifpour HMosleh MKheyrandish M(2015)An intelligent audio watermarking based on KNN learning algorithmInternational Journal of Speech Technology10.1007/s10772-015-9318-018:4(697-706)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1007/s10772-015-9318-0
Chaudhry AJaffar ASikandar BKim JIshtiaq MTuan T(2013)Genetic swarm based robust image watermarkingProceedings of the 7th International Conference on Ubiquitous Information Management and Communication10.1145/2448556.2448562(1-7)Online publication date: 17-Jan-2013
https://dl.acm.org/doi/10.1145/2448556.2448562
Show More Cited By

Recommendations

A robust digital audio watermarking based on statistics characteristics

In digital audio watermarking, the watermark's vulnerability to desynchronization attacks has long been a difficult problem. According to the audio statistics characteristics and synchronization code technique, a new robust audio watermarking scheme ...
A robust content based audio watermarking using UDWT and invariant histogram

Desynchronization attack is known as one of the most difficult attacks to resist, for it can desynchronize the location of the watermark and hence causes incorrect watermark detection. It is a challenging work to design a robust audio watermarking ...
A Robust Audio Watermarking Scheme using Higher-order Statistics in Empirical Mode Decomposition Domain

The development of a desynchronization invariant audio watermarking scheme without degrading acoustical quality is a challenging work. This paper proposes a robust audio watermarking scheme in Empirical Mode Decomposition EMD domain, in which the higher-...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Network and Computer Applications

Journal of Network and Computer Applications Volume 31, Issue 4

November, 2008

630 pages

ISSN:1084-8045

Issue’s Table of Contents

Copyright © Elsevier Ltd © 2007.

Publisher

Academic Press Ltd.

United Kingdom

Publication History

Published: 01 November 2008

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Khan AJabeen FNaz FSuhail SAhmed MNawaz S(2016)Buyer seller watermarking protocols issues and challenges A surveyJournal of Network and Computer Applications10.1016/j.jnca.2016.08.02675:C(317-334)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1016/j.jnca.2016.08.026
Latifpour HMosleh MKheyrandish M(2015)An intelligent audio watermarking based on KNN learning algorithmInternational Journal of Speech Technology10.1007/s10772-015-9318-018:4(697-706)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1007/s10772-015-9318-0
Chaudhry AJaffar ASikandar BKim JIshtiaq MTuan T(2013)Genetic swarm based robust image watermarkingProceedings of the 7th International Conference on Ubiquitous Information Management and Communication10.1145/2448556.2448562(1-7)Online publication date: 17-Jan-2013
https://dl.acm.org/doi/10.1145/2448556.2448562
Peng HLi BLuo XWang JZhang Z(2013)A learning-based audio watermarking scheme using kernel Fisher discriminant analysisDigital Signal Processing10.1016/j.dsp.2012.08.00623:1(382-389)Online publication date: 1-Jan-2013
https://dl.acm.org/doi/10.1016/j.dsp.2012.08.006
Chang CWang HShen W(2010)Copyright-proving scheme for audio with counter-propagation neural networksDigital Signal Processing10.1016/j.dsp.2009.12.00120:4(1087-1101)Online publication date: 1-Jul-2010
https://dl.acm.org/doi/10.1016/j.dsp.2009.12.001
Garcia-Crespo AGomez-Berbis JColomo-Palacios RGarcia-Sanchez F(2009)Using Support Vector Machines for feature-oriented profile-based recommendationsInternational Journal of Advanced Intelligence Paradigms10.1504/IJAIP.2009.0267621:4(418-431)Online publication date: 1-Jun-2009
https://dl.acm.org/doi/10.1504/IJAIP.2009.026762

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents