Selection-channel-aware rich model for Steganalysis of digital images

@article{Denemark2014SelectionchannelawareRM,
  title={Selection-channel-aware rich model for Steganalysis of digital images},
  author={Tom{\'a}s Denemark and Vahid Sedighi and Vojtech Holub and R{\'e}mi Cogranne and Jessica J. Fridrich},
  journal={2014 IEEE International Workshop on Information Forensics and Security (WIFS)},
  year={2014},
  pages={48-53}
}
From the perspective of signal detection theory, it seems obvious that knowing the probabilities with which the individual cover elements are modified during message embedding (the so-called probabilistic selection channel) should improve steganalysis. It is, however, not clear how to incorporate this information into steganalysis features when the detector is built as a classifier. In this paper, we propose a variant of the popular spatial rich model (SRM) that makes use of the selection… CONTINUE READING
Highly Influential
This paper has highly influenced 12 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 128 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 87 extracted citations

Adaptive Steganalysis Based on Selection Region and Combined Convolutional Neural Networks

Security and Communication Networks • 2017
View 6 Excerpts
Highly Influenced

Ensemble of CNN and rich model for steganalysis

2017 International Conference on Systems, Signals and Image Processing (IWSSIP) • 2017
View 7 Excerpts
Highly Influenced

A distortion cost modification strategy for adaptive pentary steganography

Multimedia Tools and Applications • 2016
View 7 Excerpts
Highly Influenced

Adaptive Steganalysis Based on Embedding Probabilities of Pixels

IEEE Transactions on Information Forensics and Security • 2016
View 9 Excerpts
Highly Influenced

Decomposing Joint Distortion for Adaptive Steganography

IEEE Transactions on Circuits and Systems for Video Technology • 2017
View 4 Excerpts
Highly Influenced

Multi-channel neural network for steganalysis

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) • 2017
View 4 Excerpts
Highly Influenced

Rethinking Optimal Embedding

View 6 Excerpts
Highly Influenced

A Strategy of Clustering Modification Directions in Spatial Image Steganography

IEEE Transactions on Information Forensics and Security • 2015
View 6 Excerpts
Highly Influenced

128 Citations

0204020152016201720182019
Citations per Year
Semantic Scholar estimates that this publication has 128 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 21 references

Universal distortion design for steganography in an arbitrary domain

V. Holub, J. Fridrich
EURASIP Journal on Information Security, Special Issue on Revised Selected Papers of the 1st ACM IH and MMS Workshop, 2014:1, • 2014
View 16 Excerpts
Highly Influenced

Detection of content adaptive LSB matching: a game theory approach

Media Watermarking, Security, and Forensics • 2014
View 1 Excerpt

Further study on the security of S-UNIWARD

Media Watermarking, Security, and Forensics • 2014
View 2 Excerpts

Designing steganographic distortion using directional filters

2012 IEEE International Workshop on Information Forensics and Security (WIFS) • 2012
View 14 Excerpts

Ensemble Classifiers for Steganalysis of Digital Media

IEEE Transactions on Information Forensics and Security • 2012
View 1 Excerpt

Similar Papers

Loading similar papers…