An adaptive and large payload audio watermarking against jittering attacks

Tianyu Yang, Canghong Shi*, Minfeng Shao, Sani M. Abdullahi, Imran Mumtaz, Yong Liu, Ling Xiong

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

In most watermarking algorithms, the choice of parameters directly affects the performance of the algorithms, and they are not resistant to the jittering attacks or have insufficient capacity. To address the effect of parameters on performance, inadequate capacity, and jittering attacks of digital watermarking, we propose a high-capacity and adaptive watermarking based on Shamir secret sharing. By applying improved Shamir secret sharing encryption, one of the generated shares serves as the encrypted watermark. This enables the recovery of the original watermark by embedding only one-third of the total watermark information. Then, we embed and extract the encrypted watermark by calculating the ratio of the singular values of the front and back segments of each frame of the first-level Discrete Wavelet Transform (DWT) approximation coefficients. We also derived the optimal modification method in the embedding process using the signal-to-noise ratio (SNR) formula which further optimizes the performance of the proposed algorithm. Compared with state-of-the-art audio watermarking algorithms, the proposed algorithm is more robust and has higher capacity. The average value of the bit error rate (BER) is lower than 10% when the value of SNR is greater than 20 dB. For jittering attacks, the proposed scheme achieves an average BER of 2.34%. Additionally, the watermarking capacity reaches 128 bits per second (bps) and the watermarking scheme can efficiently defend against the jittering attack.

Original languageEnglish
Article number110321
JournalComputers and Electrical Engineering
Volume124
ISSN0045-7906
DOIs
Publication statusPublished - May 2025

Keywords

  • Adaptive
  • Audio watermarking
  • Discrete wavelet transform(DWT)
  • Shamir secret sharing
  • Singular value decomposition(SVD)

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