research-article

Calibration revisited

Authors:

Jessica FridrichAuthors Info & Claims

MM&Sec '09: Proceedings of the 11th ACM workshop on Multimedia and security

Pages 63 - 74

https://doi.org/10.1145/1597817.1597830

Published: 07 September 2009 Publication History

Abstract

Calibration was first introduced in 2002 as a new concept to attack the F5 algorithm [3]. Since then, it became an essential part of many feature-based blind and targeted steganalyzers in JPEG as well as spatial domain. The purpose of this paper is to shed more light on how, why, and when calibration works. In particular, this paper challenges the thesis that the purpose of calibration is to estimate cover image features from the stego image. We classify calibration according to its internal mechanism into several canonical examples, including the case when calibration hurts the detection performance. All examples are demonstrated on specific steganographic schemes and steganalysis features. Furthermore, we propose a modified calibration procedure that improves practical steganalysis.

References

[1]

J. Fridrich. Feature-based steganalysis for JPEG images and its implications for future design of steganographic schemes. In J. Fridrich, editor, Information Hiding, 6th International Workshop, volume 3200 of Lecture Notes in Computer Science, pages 67--81, Toronto, Canada, May 23-25, 2004. Springer-Verlag, New York.

Digital Library

[2]

J. Fridrich and M. Goljan. On estimation of secret message length in LSB steganography in spatial domain. In E. J. Delp and P. W. Wong, editors, Proceedings SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents VI, volume 5306, pages 23--34, San Jose, CA, January 19--22, 2004.

[3]

J. Fridrich, M. Goljan, and D. Hogea. Steganalysis of JPEG images: Breaking the F5 algorithm. In Information Hiding, 5th International Workshop, volume 2578 of Lecture Notes in Computer Science, pages 310--323, Noordwijkerhout, The Netherlands, October 7-9, 2002. Springer-Verlag, New York.

Digital Library

[4]

J. Fridrich, M. Goljan, D. Hogea, and D. Soukal. Quantitative steganalysis of digital images: Estimating the secret message length. ACM Multimedia Systems Journal, 9(3):288--302, 2003.

Digital Library

[5]

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

[6]

S. Hetzl and P. Mutzel. A graph-theoretic approach to steganography. In J. Dittmann, S. Katzenbeisser, and A. Uhl, editors, Communications and Multimedia Security, 9th IFIP TC-6 TC-11 International Conference, CMS 2005, volume 3677 of Lecture Notes in Computer Science, pages 119--128, Salzburg, Austria, September 19--21, 2005.

Digital Library

[7]

S. S. Keerthi, V. Sindhwani, and O. Chapelle. An efficient method for gradient-based adaptation of hyperparameters in svm models. In B. Schölkopf, J. Platt, and T. Hoffman, editors, Advances in Neural Information Processing Systems 19, pages 673--680. MIT Press, Cambridge, MA, 2007.

[8]

A. D. Ker. Improved detection of LSB steganography in grayscale images. In J. Fridrich, editor, Information Hiding, 6th International Workshop, volume 3200 of Lecture Notes in Computer Science, pages 97--115, Toronto, Canada, May 23--25, 2004. Springer-Verlag, Berlin.

Digital Library

[9]

A. D. Ker. Resampling and the detection of LSB matching in color bitmaps. In E. J. Delp and P. W. Wong, editors, Proceedings SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents VII, volume 5681, pages 1--15, San Jose, CA, January 16-20, 2005.

[10]

A. D. Ker. Steganalysis of LSB matching in grayscale images. IEEE Signal Processing Letters, 12(6):441--444, June 2005.

[11]

A. D. Ker, T. Pevný, J. Kodovský, and J. Fridrich. The Square Root Law of steganographic capacity. In A. D. Ker, J. Dittmann, and J. Fridrich, editors, Proceedings of the 10th ACM Multimedia&Security Workshop, pages 107--116, Oxford, UK, September 22--23, 2008.

Digital Library

[12]

Y. Kim, Z. Duric, and D. Richards. Modified matrix encoding technique for minimal distortion steganography. In J. L. Camenisch, C. S. Collberg, N. F. Johnson, and P. Sallee, editors, Information Hiding, 8th International Workshop, volume 4437 of Lecture Notes in Computer Science, pages 314--327, Alexandria, VA, July 10-12, 2006. Springer-Verlag, New York.

Digital Library

[13]

J. Kodovský and J. Fridrich. Influence of embedding strategies on security of steganographic methods in the JPEG domain. In E. J. Delp and P. W. Wong, editors, Proceedings SPIE, Electronic Imaging, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, volume 6819, pages 2-1--2-13, San Jose, CA, January 27-31, 2008.

[14]

J. Kodovský, J. Fridrich, and T. Pevný. Statistically undetectable JPEG steganography: Dead ends, challenges, and opportunities. In J. Dittmann and J. Fridrich, editors, Proceedings of the 9th ACM Multimedia&Security Workshop, pages 3--14, Dallas, TX, September 20-21, 2007.

Digital Library

[15]

K. Lee and A. Westfeld. Generalized category attack - improving histogram-based attack on JPEG LSB embedding. In T. Furon, F. Cayre, G. Doërr, and P. Bas, editors, Information Hiding, 9th International Workshop, volume 4567 of Lecture Notes in Computer Science, pages 378--392, Saint Malo, France, June 11-13, 2007. Springer-Verlag, Berlin.

Digital Library

[16]

Bin Li, Yun Q. Shi, and Jiwu Huang. Steganalysis of yass. In A. D. Ker, J. Dittmann, and J. Fridrich, editors, Proceedings of the 10th ACM Multimedia&Security Workshop, pages 139--148, Oxford, UK, September 22-23, 2008.

Digital Library

[17]

T. Pevný and J. Fridrich. Merging Markov and DCT features for multi-class JPEG steganalysis. In E. J. Delp and P. W. Wong, editors, Proceedings SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents IX, volume 6505, pages 3 1--3 14, San Jose, CA, January 29 - February 1, 2007.

[18]

T. Pevný and J. Fridrich. Benchmarking for steganography. In K. Solanki, K. Sullivan, and U. Madhow, editors, Information Hiding, 10th International Workshop, volume 5284 of Lecture Notes in Computer Science, Santa Barbara, CA, June 19-21, 2008. Springer-Verlag, New York.

Digital Library

[19]

N. Provos. Defending against statistical steganalysis. In 10th USENIX Security Symposium, pages 323--335, Washington, DC, August 13-17, 2001.

Digital Library

[20]

A. Sarkar, K. Solanki, and B. S. Manjunath. Further study on YASS: Steganography based on randomized embedding to resist blind steganalysis. In E. J. Delp and P. W. Wong, editors, Proceedings SPIE, Electronic Imaging, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, volume 6819, pages 16--31, San Jose, CA, January 27-31, 2008.

[21]

Y. Q. Shi, C. Chen, and W. Chen. A Markov process based approach to effective attacking JPEG steganography. In J. L. Camenisch, C. S. Collberg, N. F. Johnson, and P. Sallee, editors, Information Hiding, 8th International Workshop, volume 4437 of Lecture Notes in Computer Science, pages 249--264, Alexandria, VA, July 10-12, 2006. Springer-Verlag, New York.

Digital Library

[22]

K. Solanki, A. Sarkar, and B. S. Manjunath. YASS: Yet another steganographic scheme that resists blind steganalysis. In T. Furon, F. Cayre, G. Doërr, and P. Bas, editors, Information Hiding, 9th International Workshop, volume 4567 of Lecture Notes in Computer Science, pages 16--31, Saint Malo, France, June 11--13, 2007. Springer-Verlag, New York.

Digital Library

[23]

D. Upham. Steganographic algorithm JSteg. http://zooid.org/ paul/crypto/jsteg.

[24]

A. Westfeld. High capacity despite better steganalysis (F5 - a steganographic algorithm). In I. S. Moskowitz, editor, Information Hiding, 4th International Workshop, volume 2137 of Lecture Notes in Computer Science, pages 289--302, Pittsburgh, PA, April 25-27, 2001. Springer-Verlag, New York.

Digital Library

Cited By

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
Yao YHuang LWang HChang QRen YXiao F(2024)Robust Adaptive Steganography Based on Adaptive STC-ECCIEEE Transactions on Multimedia10.1109/TMM.2023.333448726(5477-5489)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2023.3334487
Zeng KChen KZhang WWang Y(2024)Upward Robust Steganography Based on Overflow AlleviationIEEE Transactions on Multimedia10.1109/TMM.2023.326462826(299-312)Online publication date: 2024
https://doi.org/10.1109/TMM.2023.3264628
Show More Cited By

Index Terms

Calibration revisited
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

Recommendations

Steganalysis of YASS
MM&Sec '08: Proceedings of the 10th ACM workshop on Multimedia and security

In this paper, we describe a method for attacking Yet Another Steganographic Scheme (YASS), which is designed to be a very secure JPEG steganographic algorithm. The success of YASS is attributed to its innovation in embedding, i.e., hiding data in ...
Steganalysis of YASS

A promising steganographic method--Yet Another Steganography Scheme (YASS)--was designed to resist blind steganalysis via embedding data in randomized locations. In addition to a concrete realization which is named the YASS algorithm in this paper, a ...
Improved Approaches with Calibrated Neighboring Joint Density to Steganalysis and Seam-Carved Forgery Detection in JPEG Images
Special Sections on Diversity and Discovery in Recommender Systems, Online Advertising and Regular Papers

Steganalysis and forgery detection in image forensics are generally investigated separately. We have designed a method targeting the detection of both steganography and seam-carved forgery in JPEG images. We analyze the neighboring joint density of the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

MM&Sec '09: Proceedings of the 11th ACM workshop on Multimedia and security

September 2009

186 pages

ISBN:9781605584928

DOI:10.1145/1597817

General Chair:
Edward W. Felten
Center for Information Technology Policy, Princeton University USA
,
Program Chairs:
Jana Dittmann
Otto-von-Guericke University Magdeburg, Germany
,
Jessica Fridrich
SUNY Binghamton, USA
,
Scott Craver
SUNY Binghamton, USA

Copyright © 2009 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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 September 2009

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

MM&Sec '09

Sponsor:

MM&Sec '09: Multimedia and Security Workshop

September 7 - 8, 2009

New Jersey, Princeton, USA

Acceptance Rates

Overall Acceptance Rate 128 of 318 submissions, 40%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

182
Total Citations
View Citations
526
Total Downloads

Downloads (Last 12 months)61
Downloads (Last 6 weeks)14

Reflects downloads up to 09 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

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
Yao YHuang LWang HChang QRen YXiao F(2024)Robust Adaptive Steganography Based on Adaptive STC-ECCIEEE Transactions on Multimedia10.1109/TMM.2023.333448726(5477-5489)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2023.3334487
Zeng KChen KZhang WWang Y(2024)Upward Robust Steganography Based on Overflow AlleviationIEEE Transactions on Multimedia10.1109/TMM.2023.326462826(299-312)Online publication date: 2024
https://doi.org/10.1109/TMM.2023.3264628
Ma YXu LZhang YZhang TLuo X(2024)Steganalysis Feature Selection With Multidimensional Evaluation and Dynamic Threshold AllocationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2023.329536434:3(1954-1969)Online publication date: Mar-2024
https://doi.org/10.1109/TCSVT.2023.3295364
Liu XLi WLin KLi B(2024)Spatial-Frequency Feature Fusion Network for Lightweight and Arbitrary-Sized JPEG SteganalysisIEEE Signal Processing Letters10.1109/LSP.2024.346217431(2585-2589)Online publication date: 2024
https://doi.org/10.1109/LSP.2024.3462174
Huang XCao YOhtsuki T(2024)Deep Sub-Image Sampling Based Defense Against Spatial-Domain Adversarial Steganography2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)10.1109/ICASSPW62465.2024.10627039(383-387)Online publication date: 14-Apr-2024
https://doi.org/10.1109/ICASSPW62465.2024.10627039
Yu XMa YZhang YLi XZhao Y(2024)Fast dominant feature selection with compensation for efficient image steganalysisSignal Processing10.1016/j.sigpro.2024.109475220(109475)Online publication date: Jul-2024
https://doi.org/10.1016/j.sigpro.2024.109475
Gupta AChhikara RSharma P(2024)Embedded Feature Selection Approach Using Penalized Logistic Regression for Universal SteganalysisProcedia Computer Science10.1016/j.procs.2024.04.150235(1590-1599)Online publication date: 2024
https://doi.org/10.1016/j.procs.2024.04.150
Zhao NChen KQin CYin YZhang WYu NMoreira DBharati APasquini CYousfi Y(2023)Calibration-based Steganalysis for Neural Network SteganographyProceedings of the 2023 ACM Workshop on Information Hiding and Multimedia Security10.1145/3577163.3595100(91-96)Online publication date: 28-Jun-2023
https://dl.acm.org/doi/10.1145/3577163.3595100
Ma YYu XLuo XLiu DZhang Y(2023)Adaptive feature selection for image steganalysis based on classification metricsInformation Sciences10.1016/j.ins.2023.118973(118973)Online publication date: Apr-2023
https://doi.org/10.1016/j.ins.2023.118973
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents