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Batch steganography in the real world

Authors:

Andrew David Ker,

Tomas PevnyAuthors Info & Claims

MM&Sec '12: Proceedings of the on Multimedia and security

Pages 1 - 10

https://doi.org/10.1145/2361407.2361409

Published: 06 September 2012 Publication History

Abstract

We examine the universal pooled steganalyzer of in two respects. First, we confirm that the method is applicable to a number of different steganographic embedding methods. Second, we consider the converse problem of how to spread payload between multiple covers, by testing different payload allocation strategies against the universal steganalyzer. We focus on practical options which can be implemented without new software or expert knowledge, and we test on real-world data. Concentration of payload into the minimal number of covers is consistently the least detectable option. We present additional investigations which explain this phenomenon, uncovering a nonlinear relationship between embedding distortion and payload. We conjecture that this is an unavoidable consequence of blind steganalysis. This is significant for both batch steganography and pooled steganalysis.

References

[1]

M. M. Breunig, H.-P. Kriegel, R. T. Ng, and J. Sander. Lof: Identifying density-based local outliers. In Proc. 2000 ACM SIGMOD International Conference on Management of Data, SIGMOD, pages 93--104. ACM, 2000.

Digital Library

[2]

T. Filler and J. Fridrich. Gibbs construction in steganography. IEEE Transactions on Information Forensics and Security, 5(4):705--720, 2010.

Digital Library

[3]

T. Filler and J. Fridrich. Minimizing additive distortion functions with non-binary embedding operation in steganography. In Information Forensics and Security (WIFS), 2010 IEEE International Workshop on, pages 1--6, 2010.

[4]

T. Filler and J. Fridrich. Design of adaptive steganographic schemes for digital images. In N. D. Memon, J. Dittmann, A. M. Alattar, and E. J. Delp III, editors, Media Watermarking, Security, and Forensics XIV, volume 7880 of Proc. SPIE, page 78800F. SPIE, 2011.

[5]

T. Filler, J. Judas, and J. Fridrich. Minimizing additive distortion in steganography using syndrome-trellis codes. IEEE Transactions on Information Forensics and Security, 6(3):920--935, 2011.

Digital Library

[6]

J. Fridrich, M. Goljan, and D. Soukal. Wet paper codes with improved embedding efficiency. IEEE Transactions on Information Forensics and Security, 1(1):102--110, 2006.

Digital Library

[7]

J. Fridrich, T. Pevný, and J. Kodovský. Statistically undetectable JPEG steganography: Dead ends challenges, and opportunities. In Proc. 9th ACM Workshop on Multimedia and Security, MM&Sec, pages 3--14. ACM, 2007.

Digital Library

[8]

A. Gretton, K. M. Borgwardt, M. J. Rasch, B. Schölkopf, and A. J. Smola. A kernel method for the two-sample problem. pages 513--520, 2007.

[9]

S. Hetzl. Implementation of the Steghide algorithm ver. 0.5.1 (released October 2003). http://steghide.sourceforge.net/, last accessed April 2012.

[10]

S. Hetzl and P. Mutzel. A graph-theoretic approach to steganography. In Proc. 9th International Conference on Communications and Multimedia Security, CMS, pages 119--128. Springer, 2005.

Digital Library

[11]

A. D. Ker. Batch steganography and pooled steganalysis. In J. Camenisch, C. Collberg, N. Johnson, and P. Sallee, editors, Proc. 8th Information Hiding Workshop, volume 4437 of LNCS, pages 265--281. Springer, 2006.

Digital Library

[12]

A. D. Ker. Batch steganography and the threshold game. In E. Delp III and P. Wong, editors, Security, Steganography, and Watermarking of Multimedia Contents IX, volume 6505 of Proc. SPIE, pages 0401--0413. SPIE, 2007.

[13]

A. D. Ker. Perturbation hiding and the batch steganography problem. In K. Solanki, K. Sullivan, and U. Madhow, editors, Proc. 10th Information Hiding Workshop, volume 5284 of LNCS, pages 45--59. Springer, 2008.

Digital Library

[14]

A. D. Ker and T. Pevný. A new paradigm for steganalysis via clustering. In N. Memon, J. Dittmann, A. Alattar, and E. Delp III, editors, Media Watermarking, Security, and Forensics XIII, volume 7880 of Proc. SPIE, pages 0U01--0U13. SPIE, 2011.

[15]

A. D. Ker and T. Pevný. Identifying a steganographer in realistic and heterogeneous data sets. In N. Memon, A. Alattar, and E. Delp III, editors, Media Watermarking, Security, and Forensics XIV, volume 8303 of Proc. SPIE, pages 0N01--0N13. SPIE, 2012.

[16]

J. Kodovský. simulator of the nsF5 algorithm with wet paper codes (released 2008). http://dde.binghamton.edu/download/nsf5simulator/, last accessed April 2012.

[17]

A. Latham. Implementation of the JPHide and JPSeek algorithms ver 0.3 (released August 1999). http://linux01.gwdg.de/ alatham/stego.html, last accessed April 2012.

[18]

T. Pevný, T. Filler, and P. Bas. Using high-dimensional image models to perform highly undetectable steganography. In P. W. L. Fong, R. Böhme, and R. Safavi-Naini, editors, Proc. 12th Information Hiding Workshop, volume 6387 of LNCS, pages 161--177. Springer, 2010.

Digital Library

[19]

T. Pevný and J. Fridrich. Merging Markov and DCT features for multi-class JPEG steganalysis. In E. J. Delp III and P. W. Wong, editors, Media Watermarking, Security, and Forensics IX, volume 6505, pages 03--14. SPIE, 2007.

[20]

T. Pevný, J. Fridrich, and A. D. Ker. From blind to quantitative steganalysis. Information Forensics and Security, IEEE Transactions on, 7(2):445--454, 2012.

Digital Library

[21]

N. Provos. Defending against statistical steganalysis. In Proc. 10th Conference on USENIX Security Symposium - Volume 10, SSYM, pages 323--335. USENIX Association, 2001.

Digital Library

[22]

N. Provos. Implementation of the OutGuess algorithm ver. 2.0 (released October 2001). http://www.outguess.org/, last accessed April 2012.

[23]

D. Upham. Implementation of the JSteg steganographic algorithm. http://zooid.org/ paul/crypto/jsteg/, last accessed on April 2012.

[24]

A. Westfeld. F5-a steganographic algorithm. In I. Moskowitz, editor, Proc. 4th Information Hiding Workshop, volume 2137 of LNCS, pages 289--302. Springer, 2001.

Digital Library

[25]

A. Westfeld. Implementation of the F5 steganographic algorithm (released May 2011). http://code.google.com/p/f5-steganography/, last accessed April 2012.

Cited By

Mallet ABeneš MCogranne R(2024)Cover-source mismatch in steganalysis: systematic reviewEURASIP Journal on Information Security10.1186/s13635-024-00171-62024:1Online publication date: 12-Aug-2024
https://doi.org/10.1186/s13635-024-00171-6
Kombrink MGeradts ZWorring M(2024)Image Steganography Approaches and Their Detection Strategies: A SurveyACM Computing Surveys10.1145/369496557:2(1-40)Online publication date: 10-Oct-2024
https://dl.acm.org/doi/10.1145/3694965
Dworetzky EKaziakhmedov EFridrich JPérez-González FComesaña-Alfaro PKrätzer CVicky Zhao H(2024)Improving Steganographic Security with Source BiasingProceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security10.1145/3658664.3659646(19-30)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3658664.3659646
Show More Cited By

Index Terms

Batch steganography in the real world
1. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Software architectures

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Information & Contributors

Information

Published In

cover image ACM Conferences

MM&Sec '12: Proceedings of the on Multimedia and security

September 2012

184 pages

ISBN:9781450314176

DOI:10.1145/2361407

General Chair:
Chang-Tsun Li
University of Warwick, UK
,
Program Chairs:
Jana Dittmann
Otto-von-Guericke University, Germany
,
Stefan Katzenbeisser
Technische Universität Darmstadt, Germany
,
Scott Carver
SUNY Binghamton, USA

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 September 2012

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MM&Sec '12

Sponsor:

SIGMM

MM&Sec '12: Multimedia and Security Workshop

September 6 - 7, 2012

Coventry, United Kingdom

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Overall Acceptance Rate 128 of 318 submissions, 40%

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Citations

Cited By

Mallet ABeneš MCogranne R(2024)Cover-source mismatch in steganalysis: systematic reviewEURASIP Journal on Information Security10.1186/s13635-024-00171-62024:1Online publication date: 12-Aug-2024
https://doi.org/10.1186/s13635-024-00171-6
Kombrink MGeradts ZWorring M(2024)Image Steganography Approaches and Their Detection Strategies: A SurveyACM Computing Surveys10.1145/369496557:2(1-40)Online publication date: 10-Oct-2024
https://dl.acm.org/doi/10.1145/3694965
Dworetzky EKaziakhmedov EFridrich JPérez-González FComesaña-Alfaro PKrätzer CVicky Zhao H(2024)Improving Steganographic Security with Source BiasingProceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security10.1145/3658664.3659646(19-30)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3658664.3659646
Dworetzky EFridrich J(2024)How to Form Bags in Batch Steganography2024 IEEE International Workshop on Information Forensics and Security (WIFS)10.1109/WIFS61860.2024.10810688(1-6)Online publication date: 2-Dec-2024
https://doi.org/10.1109/WIFS61860.2024.10810688
Beneš MBöhme R(2024)Kerckhoffs in Prison: A Study of the Steganalyst’s Knowledge2024 IEEE International Workshop on Information Forensics and Security (WIFS)10.1109/WIFS61860.2024.10810682(1-6)Online publication date: 2-Dec-2024
https://doi.org/10.1109/WIFS61860.2024.10810682
Li FSheng YWu KQin CZhang X(2024)LiDiNet: A Lightweight Deep Invertible Network for Image-in-Image SteganographyIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.346354719(8817-8831)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3463547
Tang WZhou ZLi BChoo KHuang J(2024)Joint Cost Learning and Payload Allocation With Image-Wise Attention for Batch SteganographyIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.335441119(2826-2839)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3354411
Yu JZhang JWang ZLi FZhang X(2024)Cover Selection in Encrypted ImagesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.344791334:12(13626-13641)Online publication date: Dec-2024
https://doi.org/10.1109/TCSVT.2024.3447913
Yu JLi FWang ZSi WZhang X(2024)Diverse Batch Steganography Using Model-Based Selection and Double-Layered Payload AssignmentIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.337654134:8(7785-7800)Online publication date: Aug-2024
https://doi.org/10.1109/TCSVT.2024.3376541
Singh BSur AMitra P(2024)Multi-contextual design of convolutional neural network for steganalysisMultimedia Tools and Applications10.1007/s11042-024-18545-w83:32(77247-77265)Online publication date: 23-Feb-2024
https://doi.org/10.1007/s11042-024-18545-w
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