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A universal technique to hide traces of histogram-based image manipulations

Published: 06 September 2012 Publication History

Abstract

We propose a universal counter-forensic technique for concealing traces left on the image histogram by any processing tool. Under the assumption that the forensic analysis relies on first-order statistics only (which is true in many practical applications), the proposed scheme allows the attacker to conceal traces left by any processing operation, while maintaining a high fidelity between processed and "cleaned" images.

References

[1]
M. Barni. A game theoretic approach to source identification with known statistics. In Proc. of ICASSP 2012, IEEE Int. Conference on Acoustics, Speech, and Signal Processing, 2012.
[2]
P. Bonami, M. Kilinc, J. Linderoth, et al. Algorithms and software for convex mixed integer nonlinear programs. Technical report, Computer Sciences Department, University of Wisconsin-Madison, 2009.
[3]
M. Bussieck and A. Pruessner. Mixed-integer nonlinear programming. SIAG/OPT Newsletter: Views & News, 14(1):19--22, 2003.
[4]
G. Cao, Y. Zhao, R. Ni, and H. Tian. Anti-forensics of contrast enhancement in digital images. In Proceedings of MM&Sec 2010, 12th ACM workshop on Multimedia and security (MM&Sec '10), 2010.
[5]
T. M. Cover and J. A. Thomas. Elements of information theory. Wiley-Interscience, New York, NY, USA, 1991.
[6]
M. J. Huiskes and M. S. Lew. The MIR Flickr retrieval evaluation. In Proc. of MIR '08, ACM International Conference on Multimedia Information Retrieval, New York, NY, USA, 2008. ACM.
[7]
M. Kirchner and R. Böhme. Tamper hiding: Defeating image forensics. In Proc of IH 2007, Int. Conference on Information Hiding, pages 326--341, 2007.
[8]
A. A. Michelson. Studies in optics. University of Chicago Press, 1927.
[9]
O. Pele and M. Werman. The Quadratic-Chi histogram distance family. In Proc. of ECCV 2010, European Conference on Computer Vision, 2010.
[10]
J. Redi, W. Taktak, and J.-L. Dugelay. Digital image forensics: a booklet for beginners. Multimedia Tools and Applications, 51:133--162, 2011. 10.1007/s11042-010-0620-1.
[11]
Y. Rubner, C. Tomasi, and L. J. Guibas. The earth mover's distance as a metric for image retrieval. International Journal of Computer Vision, 40(2):99--121, 2000.
[12]
G. Schaefer. An uncompressed benchmark image dataset for colour imaging. In Proc. of ICIP 2010, IEEE Int. Conference on Image Processing, pages 3537--3540, 2010.
[13]
M. Stamm and K. Liu. Anti-forensics for frame deletion/addition in mpeg video. In Proc. of ICASSP 2011, IEEE Int. Conference on Acoustics, Speech and Signal Processing, pages 1876--1879, 2011.
[14]
M. Stamm, S. Tjoa, W. Lin, and K. Liu. Undetectable image tampering through jpeg compression anti-forensics. In Proc. of ICIP 2010, IEEE Int. Conference on Image Processing, pages 2109--2112, 2010.
[15]
M. C. Stamm, S. Lin, and K. J. R. Liu. Forensics vs. anti-forensics: A decision and game theoretic framework. In Proc. of ICASSP 2012, IEEE Int. Conference on Acoustics, Speech, and Signal Processing, 2012.
[16]
M. C. Stamm and K. J. R. Liu. Blind forensics of contrast enhancement in digital images. In Proc. of ICIP 2008, IEEE Int. Conference on Image Processing, pages 3112--3115, 2008.
[17]
M. C. Stamm and K. J. R. Liu. Forensic detection of image manipulation using statistical intrinsic fingerprints. IEEE Transactions on Information Forensics and Security, 5(3):492--506, 2010.
[18]
M. C. Stamm and K. J. R. Liu. Wavelet-based image compression anti-forensics. In Proc. of ICIP 2010, IEEE Int. Conference on Image Processing, pages 1737--1740, 2010.
[19]
M. C. Stamm, S. K. Tjoa, W. S. Lin, and K. J. R. Liu. Anti-forensics of JPEG compression. In Proc. of ICASSP 2010, IEEE Int. Conference on Acoustics, Speech, and Signal Processing, pages 1694--1697, 2010.
[20]
G. Valenzise, V. Nobile, M. Tagliasacchi, and S. Tubaro. Countering jpeg anti-forensics. In Proc. of ICIP 2011, IEEE Int. Conference on Image Processing, pages 1949--1952, 2011.
[21]
C. Villani. Topics in optimal transportation. American Mathematical Society, 2003.
[22]
W. Wang and H. Farid. Exposing digital forgeries in video by detecting double MPEG compression. In Proc. of MM&Sec 2006, 8th ACM workshop on Multimedia & Security, pages 37--47, 2006.
[23]
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 13(4):600--612, 2004.

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      cover image ACM Conferences
      MM&Sec '12: Proceedings of the on Multimedia and security
      September 2012
      184 pages
      ISBN:9781450314176
      DOI:10.1145/2361407
      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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      Publication History

      Published: 06 September 2012

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      Author Tags

      1. contrast enhancement
      2. histogram
      3. universal counter forensics

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      MM&Sec '12
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      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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      Cited By

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      • (2024)A Bit-Plane Slicing Technique for the Classification of Anti-forensically Contrast-Enhanced Images2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT)10.1109/IC2PCT60090.2024.10486790(1619-1623)Online publication date: 9-Feb-2024
      • (2023)Multi-scale Target-Aware Framework for Constrained Splicing Detection and LocalizationProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3613763(8790-8798)Online publication date: 26-Oct-2023
      • (2023)On the Security of the One-and-a-Half-Class Classifier for SPAM Feature-Based Image ForensicsIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.326616818(2466-2479)Online publication date: 2023
      • (2023)An approach for anti-forensic contrast enhancement detection using grey level co-occurrence matrix and Zernike momentsInternational Journal of Information Technology10.1007/s41870-023-01191-015:3(1625-1636)Online publication date: 16-Mar-2023
      • (2023)Refined GAN-Based Attack Against Image Splicing Detection and Localization AlgorithmsAdversarial Multimedia Forensics10.1007/978-3-031-49803-9_4(93-123)Online publication date: 15-Nov-2023
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      • (2020)Security Attacks and Defenses in Distributed Sensor NetworksInformation Fusion in Distributed Sensor Networks with Byzantines10.1007/978-981-32-9001-3_3(29-43)Online publication date: 15-Jul-2020
      • (2020)The Appraised Structure for Improving Quality in the Compressed Image Using EQI-AC AlgorithmImage Processing and Capsule Networks10.1007/978-3-030-51859-2_19(201-217)Online publication date: 24-Jul-2020
      • (2019)Analysis of Forensic Fingerprints in Facebook Images, the Universal Antiforensic AttackProceedings of the 3rd International Conference on Video and Image Processing10.1145/3376067.3376088(228-232)Online publication date: 20-Dec-2019
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