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Effect of JPEG Quality on Steganographic Security

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Jessica FridrichAuthors Info & Claims

IH&MMSec'19: Proceedings of the ACM Workshop on Information Hiding and Multimedia Security

July 2019

Pages 47 - 56

https://doi.org/10.1145/3335203.3335714

Published: 02 July 2019 Publication History

Abstract

Abstract This work investigates both theoretically and experimentally the security of JPEG steganography as a function of the quality factor. For a fixed relative payload, modern embedding schemes, such as J-UNIWARD and UED-JC, exhibit surprising non-monotone trends due to rounding and clipping of quantization steps. Their security generally increases with increasing quality factor but starts decreasing for qualities above 95. In contrast, old-fashion steganography, such as Jsteg, OutGuess, and model-based steganography, exhibit complementary trends. The results of empirical detectors closely match the trends exhibited by the KL divergence computed between models of cover and stego DCT modes. In particular, our analysis shows that the main reason for the complementary trends is the way modern schemes attenuate embedding change rates with increasing spatial frequency. Our model also provides guidance on how to adjust the embedding algorithm J-UNIWARD to substantially improve its security for high quality factors.

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Cited By

Zeng KChen KZhang JZhang WYu N(2024)Toward Secure and Robust Steganography for Black-Box Generated ImagesIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.336122019(3237-3250)Online publication date: 2024
https://doi.org/10.1109/TIFS.2024.3361220
Pan YNi JLiu QSu WHuang J(2024)Efficient JPEG image steganography using pairwise conditional random field modelSignal Processing10.1016/j.sigpro.2024.109493221:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.sigpro.2024.109493
Mathur VLustig CKaziunas E(2022)Disordering DatasetsProceedings of the ACM on Human-Computer Interaction10.1145/35551416:CSCW2(1-33)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555141
Show More Cited By

Index Terms

Effect of JPEG Quality on Steganographic Security
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation

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Published In

cover image ACM Conferences

IH&MMSec'19: Proceedings of the ACM Workshop on Information Hiding and Multimedia Security

July 2019

249 pages

ISBN:9781450368216

DOI:10.1145/3335203

General Chairs:
Rémi Cogranne
Troyes University of Technology, France
,
Luisa Verdoliva
University Federico II of Naples, Italy
,
Program Chairs:
Siwei Lyu
University at Albany, New York, USA
,
Juan Pastoriza
Ecole polytechnique fédérale de Lausanne, Switzerland
,
Xinpeng Zhang
Shanghai University, China

Copyright © 2019 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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Association for Computing Machinery

New York, NY, United States

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Published: 02 July 2019

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IH&MMSec '19

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IH&MMSec '19: ACM Information Hiding and Multimedia Security Workshop

July 3 - 5, 2019

Paris, France

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Cited By

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https://doi.org/10.1109/TIFS.2024.3361220
Pan YNi JLiu QSu WHuang J(2024)Efficient JPEG image steganography using pairwise conditional random field modelSignal Processing10.1016/j.sigpro.2024.109493221:COnline publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1016/j.sigpro.2024.109493
Mathur VLustig CKaziunas E(2022)Disordering DatasetsProceedings of the ACM on Human-Computer Interaction10.1145/35551416:CSCW2(1-33)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555141
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Cogranne RGiboulot EBas P(2022)Efficient Steganography in JPEG Images by Minimizing Performance of Optimal DetectorIEEE Transactions on Information Forensics and Security10.1109/TIFS.2021.311171317(1328-1343)Online publication date: 2022
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