• DocumentCode
    49696
  • Title

    A Sparse Representation-Based Wavelet Domain Speech Steganography Method

  • Author

    Ahani, Soodeh ; Ghaemmaghami, Shahrokh ; Wang, Z. Jane

  • Author_Institution
    Dept. of Electr. Eng. & Electr. Res. Inst., Sharif Univ. of Technol., Tehran, Iran
  • Volume
    23
  • Issue
    1
  • fYear
    2015
  • fDate
    Jan. 2015
  • Firstpage
    80
  • Lastpage
    91
  • Abstract
    In this paper, we present a novel speech steganography method using discrete wavelet transform and sparse decomposition to address the undetectability concern in speech steganography. The proposed speech steganography method exploits the sparse representation to embed secret messages into higher semantic levels of the cover signal, resulting in increased undetectability. The proposed method also yields improvements on both stego signal quality and embedding capacity, which are the two major requirements of a steganography algorithm. Our experimental results illustrate that the stego signals generated by the proposed method are perceptually indistinguishable from the original cover signals, quantified by both SNR and PESQ quality measures. When compared with two well-known steganography methods, the proposed method is shown to be superior on addressing major requirements of a steganography algorithm, imperceptibility, undetectability, and capacity.
  • Keywords
    discrete wavelet transforms; signal representation; speech processing; steganography; PESQ quality measures; SNR; discrete wavelet transform; embedding capacity; sparse decomposition; sparse representation-based wavelet domain speech steganography method; stego signal quality; Dictionaries; Discrete wavelet transforms; Media; Speech; Speech processing; Data hiding; dictionary learning; discrete wavelet transform; sparse representation; speech steganography;
  • fLanguage
    English
  • Journal_Title
    Audio, Speech, and Language Processing, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    2329-9290
  • Type

    jour

  • DOI
    10.1109/TASLP.2014.2372313
  • Filename
    6963352