• DocumentCode
    980555
  • Title

    Steganalysis Frameworks of Embedding in Multiple Least-Significant Bits

  • Author

    Yang, Chunfang ; Liu, Fenlin ; Luo, Xiangyang ; Liu, Bin

  • Author_Institution
    Zhengzhou Inst. of Inf. Sci. & Technol., Zhengzhou
  • Volume
    3
  • Issue
    4
  • fYear
    2008
  • Firstpage
    662
  • Lastpage
    672
  • Abstract
    Replacement of least-significant bit plane is one of the popular steganography techniques in digital images because of its extreme simplicity. But it is more difficult to precisely estimate the rate of secret message embedded by replacement of multiple least-significant bit (MLSB) planes of a carrier object. In order to model the MLSB embedding, a lemma is introduced to prove the transition relationships among some trace subsets. Then, based on these transition relationships, two novel steganalysis frameworks are designed to detect two kinds of distinct MLSB embedding methods. A series of experiments show that the proposed steganalysis frameworks are highly sensitive to MLSB steganography, and can estimate the rate of secret message with higher accuracy. Furthermore, these frameworks can fully meet the need to distinguish stego images under low false positive rate, especially when the embedded message is short.
  • Keywords
    cryptography; data encapsulation; image processing; MLSB embedding methods; MLSB steganography; digital images; embedded message; message hiding; multiple least-significant bit embedding; multiple least-significant bits; secret message; steganalysis frameworks; stego images; Art; Detectors; Digital images; Histograms; Image analysis; Information science; Object detection; Payloads; Research and development; Steganography; Steganalysis; multiple least-significant bits (MLSBs); steganography; trace subset;
  • fLanguage
    English
  • Journal_Title
    Information Forensics and Security, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1556-6013
  • Type

    jour

  • DOI
    10.1109/TIFS.2008.2007240
  • Filename
    4668359