New steganalysis methodology: LR cube analysis for the detection of LSB steganography

Kwangsoo Lee, Changho Jung, Sangjin Lee, Jongin Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper, we present a new steganalytic technique to detect the use of LSB steganography in the gray-scale images. We are motivated by a need to research the high-dimensional joint characteristics of locally correlated samples. In the development, we used the successively adjacent n-pixel chains in the horizontal and vertical directions as the basic units of our steganalysis. The experimental results of the proposed method are described and compared with those of previous steganalytic methods. At the results, the proposed method outperformed the previous steganalytic methods and highly detected the low-rate embedding, even if any false detection were not occurred.

Original languageEnglish
Title of host publicationInformation Hiding - 7th International Workshop, IH 2005, Revised Selected Papers
PublisherSpringer Verlag
Pages312-326
Number of pages15
ISBN (Print)3540290397, 9783540290391
Publication statusPublished - 2006
Event7th International Workshop on Information Hiding, IH 2005 - Barcelona, Spain
Duration: 2005 Jun 62005 Jun 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3727 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Workshop on Information Hiding, IH 2005
CountrySpain
CityBarcelona
Period05/6/605/6/8

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lee, K., Jung, C., Lee, S., & Lim, J. (2006). New steganalysis methodology: LR cube analysis for the detection of LSB steganography. In Information Hiding - 7th International Workshop, IH 2005, Revised Selected Papers (pp. 312-326). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3727 LNCS). Springer Verlag.