A secure steganographic scheme against statistical analyses

Jeong Jae Yu, Jae Won Han, Kwang Su Lee, O. Seung Cheol, Sangjin Lee, Il Hwan Park

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Citations (Scopus)

Abstract

Westfeld[1] analyzed a. sequential LSB embedding steganography effectively through the χ2-statistical test which measures the frequencies of PoVs(pairs of values). Fridrich[2] also proposed another statistical analysis, so-called RS steganalysis by which the embedding message rate can be estimated. This method is based on the partition of pixels as three groups; Regular, Singular, Unusable groups. In this paper, we propose a new steganographic scheme which preserves the above two statistics. The proposed scheme embeds the secret message in the innocent image by randomly adding one to real pixel value or subtracting one from it, then adjusts the statistical measures to equal those of the original image.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsTon Kalker, Ingemar J. Cox, Yong Man Ro
PublisherSpringer Verlag
Pages497-507
Number of pages11
ISBN (Print)354021061X
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2939
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yu, J. J., Han, J. W., Lee, K. S., Seung Cheol, O., Lee, S., & Park, I. H. (2004). A secure steganographic scheme against statistical analyses. In T. Kalker, I. J. Cox, & Y. M. Ro (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 497-507). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2939). Springer Verlag. https://doi.org/10.1007/978-3-540-24624-4_40