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Compressive sensing based secret signals recovery for effective image Steganalysis in secure communications
H. Zhao, J.-C. Ren, J. Zhan, Y. Xiao, S.Y. Zhao, F. Lei, , C. Li
Published in Springer
2018
Volume: 78
   
Issue: 20
Pages: 29381 - 29394
Abstract
Conventional image steganalysis mainly focus on presence detection rather than the recovery of the original secret messages that were embedded in the host image. To address this issue, we propose an image steganalysis method featured in the compressive sensing (CS) domain, where block CS measurement matrix senses the transform coefficients of stego-image to reflect the statistical differences between the cover and stego- images. With multi-hypothesis prediction in the CS domain, the reconstruction of hidden signals is achieved efficiently. Extensive experiments have been carried out on five diverse image databases and benchmarked with four typical stegographic algorithms. The comprehensive results have demonstrated the efficacy of the proposed approach as a universal scheme for effective detection of stegography in secure communications whilst it has greatly reduced the numbers of features requested for secret signal reconstruction. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.
About the journal
JournalData powered by TypesetMultimedia Tools and Applications
PublisherData powered by TypesetSpringer
ISSN13807501
Open AccessNo
Concepts (4)
  •  related image
    Compressive sensing (cs)
  •  related image
    Image steganalysis
  •  related image
    Secret signal recovery
  •  related image
    Secure communication