A Robust Audio Aggregate Zero-Watermark Algorithm

Xiong, Yiqun; Wang, Rangding

doi:10.1109/itng.2009.19

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…An audio aggregation watermarking technology (AAWT) was firstly proposed in Ref. 20 for protecting a whole audio aggregation. Liu et al 21 used the labeled-codeword based on VQ and the middle-frequency DCT coefficients to propose a robust audio watermarking algorithm.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

A Novel Audio Aggregation Watermarking Algorithm Based on Copyright Protection

Wang

Jin

et al. 2014

IJCIS

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A novel algorithm of audio aggregation watermarking was proposed in this paper for copyright protection. The algorithm not only protects copyright of a single audio in audio aggregation but also protects copyright of the whole audio aggregation. The experimental results showed the watermark of aggregate audio can resist to some attacks, for example, deleting audio, and substituting audio; at the same time, watermark of every single audio is robust to some attacks such as low-filtering, resampling, requantization, noise addition and mp3 compression. The proposed algorithm has good imperceptibility strong robustness and low complexity.

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Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

A Novel Audio Aggregation Watermarking Algorithm Based on Copyright Protection

Wang

Jin

et al. 2014

IJCIS

Self Cite

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“…Furthermore, pirates are more willing to work on the entire audio aggregation for commercial interests. Therefore, watermark technology [1] that lets audio aggregation as carrier has a bright future.…”

Section: Introduction (Heading 1)mentioning

confidence: 99%

Audio aggregation zero-watermark algorithm based on (k,n/k=n)

Wang

2010

2010 2nd International Conference on Signal Processing Systems

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This paper presents an audio aggregation zerowatermark algorithm based on (k, n/k=n), which using the nature of fragile watermark to realize audio aggregation certification. Firstly, using lifting wavelet transform (LWT) technique to each audio work in the aggregation which includes n audio works. Secondly, watermark was distributed into n shares by (k, n) threshold scheme. Finally, we can get n copies of key when the n shares are conducted bitwise XOR with the high-frequency coefficients of each audio work in the aggregation, then encrypting on them to form the final key. Simultaneously, realize zero-watermark embedding. In the watermark distributed process, in order to obtain better vulnerability, k is set as n. Simulation shows that the proposed algorithm has low computational complexity, high security, strong vulnerability, and good imperceptibility.

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