Adaptive and blind audio watermarking algorithm based on dither modulation and butterfly optimization algorithm.

Qiuling Wu, Dandan Huang, Jiangchun Wei, Wenhui Chen
Author Information
  1. Qiuling Wu: School of Cyber Security, Jinling Institute of Technology, Nanjing, Jiangsu 211169, China.
  2. Dandan Huang: School of Cyber Security, Jinling Institute of Technology, Nanjing, Jiangsu 211169, China.
  3. Jiangchun Wei: Jiangsu Liyuan Power Engineering Co., Ltd., Nanjing, Jiangsu 211100, China.
  4. Wenhui Chen: School of Cyber Security, Jinling Institute of Technology, Nanjing, Jiangsu 211169, China.

Abstract

How to improve the robustness to resist attacks and how to adaptively match the key parameters of the watermarking algorithm with the performance requirements to achieve the best performance in different applications are two hot issues in the research of audio watermarking algorithms. An adaptive and blind audio watermarking algorithm based on dither modulation and butterfly optimization algorithm (BOA) is proposed. Based on the convolution operation, a stable feature is designed to carry the watermark, which will improve the robustness by means of the stability of this feature to prevent the watermark loss. Blind extraction will be achieved only by comparing the feature value and the quantized value without the original audio. The BOA is used to optimize the key parameters of the algorithm which can be matched with the performance requirements by coding the population and constructing the fitness function. Experimental results confirm that this proposed algorithm can adaptively search for the optimal key parameters that match the performance requirements. Compared with other related algorithms in recent years, it exhibits strong robustness against various signal processing attacks and synchronization attacks.

Keywords

MeSH Term

Image Interpretation, Computer-Assisted
Computer Security
Algorithms
Signal Processing, Computer-Assisted

Word Cloud

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