Audio watermarking for monitoring and copy protection
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Transparent and Robust Audio Data Hiding in Subband Domain
ITCC '00 Proceedings of the The International Conference on Information Technology: Coding and Computing (ITCC'00)
StirMark Benchmark: Audio Watermarking Attacks
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
Spread-spectrum watermarking of audio signals
IEEE Transactions on Signal Processing
Diversity and attack characterization for improved robustwatermarking
IEEE Transactions on Signal Processing
Robust audio watermarking in the time domain
IEEE Transactions on Multimedia
Digital audio watermarking in the cepstrum domain
IEEE Transactions on Consumer Electronics
Robust watermarking of audio with blind self-authentication
EHAC'08 Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications
Blind tamper detection in audio using chirp based robust watermarking
WSEAS Transactions on Signal Processing
An adaptive audio watermarking based on the singular value decomposition in the wavelet domain
Digital Signal Processing
Audio watermark detection improvement by using noise modelling
MIV'05 Proceedings of the 5th WSEAS international conference on Multimedia, internet & video technologies
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Collusion resilient spread spectrum watermarking in M-band wavelets using GA-fuzzy hybridization
Journal of Systems and Software
Wireless Personal Communications: An International Journal
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In this paper, we present a novel audio watermarking scheme that uses attack characterization to obtain high robustness against standard watermark attacks. The watermark embedding and detection are based on the frequency hopping method in the spectral domain. Perceptual transparency of the algorithm, achieved using frequency masking property of the human auditory system, was confirmed throughout listening tests. Detection robustness of the proposed scheme with and without attack characterization module was compared to standard direct sequence approach. Tests showed that the proposed method obtains higher robustness to standard watermarking attacks and that the attack characterization module significantly improves the performance of both algorithms.