A robust intelligent audio watermarking scheme using support vector machine

  • Mohammad Mosleh
  • Hadi Latifpour
  • Mohammad Kheyrandish
  • Mahdi Mosleh
  • Najmeh Hosseinpour
Article

Abstract

Rapid growth in information technology and computer networks has resulted in the universal use of data transmission in the digital domain. However, the major challenge faced by digital data owners is protection of data against unauthorized copying and distribution. Digital watermark technology is starting to be considered a credible protection method to mitigate the potential challenges that undermine the efficiency of the system. Digital audio watermarking should retain the quality of the host signal in a way that remains inaudible to the human hearing system. It should be sufficiently robust to be resistant against potential attacks. One of the major deficiencies of conventional audio watermarking techniques is the use of non-intelligent decoders in which some sets of specific rules are used for watermark extraction. This paper presents a new robust intelligent audio watermarking scheme using a synergistic combination of singular value decomposition (SVD) and support vector machine (SVM). The methodology involves embedding a watermark data by modulating the singular values in the SVD transform domain. In the extraction process, an intelligent detector using SVM is suggested for extracting the watermark data. By learning the destructive effects of noise, the detector in question can effectively retrieve the watermark. Diverse experiments under various conditions have been carried out to verify the performance of the proposed scheme. Experimental results showed better imperceptibility, higher robustness, lower payload, and higher operational efficiency, for the proposed method than for conventional techniques.

Key words

Audio watermarking Copyright protection Singular value decomposition (SVD) Machine learning Support vector machine (SVM) 

CLC number

TP391 

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Notes

Acknowledgments

The presented paper is the result of a research entitled ‘Presenting an adaptive audio watermarking scheme for increasing robustness against attacks using optimization algorithms and computational intelligent techniques’, which was sponsored by Islamic Azad University of Dezfoul and the authors hereby express their thanks.

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Copyright information

© Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Mohammad Mosleh
    • 1
  • Hadi Latifpour
    • 1
  • Mohammad Kheyrandish
    • 1
  • Mahdi Mosleh
    • 2
  • Najmeh Hosseinpour
    • 3
  1. 1.Department of Computer Engineering, Dezfoul BranchIslamic Azad UniversityDezfoulIran
  2. 2.Department of Computer Engineering, Andimeshk BranchIslamic Azad UniversityAndimeshkIran
  3. 3.Young Researchers and Elite Club, Andimeshk BranchIslamic Azad UniversityAndimeshkIran

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