A novel approach for JPEG steganography

Vasiliy Sachnev, Hyoung Joong Kim, Rongyue Zhang, Yong Soo Choi

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

4 Citations (Scopus)

Abstract

In this paper we present a novel steganography method for JPEG images. The proposed data hiding technique bases on removing and inserting AC coefficients 1 or -1. The candidates for removing and inserting are searched among all non rounded AC coefficients after quantization. The proposed search technique flags the most appropriate coefficients, which provide less degradation after modification. The proposed data hiding technique based on the modification the flagged coefficients significantly decreases distortion after data hiding and, as result, shows the less detectability for steganalysis. The proposed method was tested with steganalysis method proposed by T. Pevny and J.Fridrich. The experimental results show that the proposed method has less detectability compared to the existed widely used steganography methods as F5 and OutGuess.

Original languageEnglish
Title of host publicationDigital Watermarking - 7th International Workshop, IWDW 2008, Selected Papers
Pages209-217
Number of pages9
DOIs
Publication statusPublished - 2009
Event7th International Workshop on Digital Watermarking, IWDW 2008 - Busan, Korea, Republic of
Duration: 2008 Nov 102008 Nov 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5450 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Workshop on Digital Watermarking, IWDW 2008
CountryKorea, Republic of
CityBusan
Period08/11/1008/11/12

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Sachnev, V., Kim, H. J., Zhang, R., & Choi, Y. S. (2009). A novel approach for JPEG steganography. In Digital Watermarking - 7th International Workshop, IWDW 2008, Selected Papers (pp. 209-217). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5450 LNCS). https://doi.org/10.1007/978-3-642-04438-0_18