research-article

StegaDDPM: Generative Image Steganography based on Denoising Diffusion Probabilistic Model

Authors:

Weiming ZhangAuthors Info & Claims

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

Pages 7143 - 7151

https://doi.org/10.1145/3581783.3612514

Published: 27 October 2023 Publication History

Abstract

Image steganography is the technology of concealing secret messages within an image. Recently, generative image steganography has been developed, which conceals secret messages during image generation. However, existing generative image steganography schemes are often criticized for their poor steganographic capacity and extraction accuracy. To ensure secure and dependable communication, we propose a novel generative image steganography based on the denoising diffusion probabilistic model, called StegaDDPM. StegaDDPM utilizes the probability distribution between the intermediate state and generated image in the reverse process of the diffusion model. The secret message is hidden in the generated image through message sampling, which follows the same probability distribution as normal generation. The receiver uses two shared random seeds to reproduce the reverse process and accurately extract secret data. Experimental results show that StegaDDPM outperforms state-of-the-art methods in terms of steganographic capacity, extraction accuracy, and security. In addition, it can securely conceal and accurately extract secret messages up to 9 bits per pixel.

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Cited By

Hu MWang H(2025)Mutual Information-Optimized Steganalysis for Generative SteganographyIEEE Transactions on Information Forensics and Security10.1109/TIFS.2025.353908920(1852-1865)Online publication date: 2025
https://doi.org/10.1109/TIFS.2025.3539089
Ren CWu B(2024)A Robust joint coverless image steganography scheme based on two independent modulesCybersecurity10.1186/s42400-024-00299-57:1Online publication date: 7-Dec-2024
https://doi.org/10.1186/s42400-024-00299-5
Peng YWang YHu DChen KRong XZhang WCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)LDStega: Practical and Robust Generative Image Steganography based on Latent Diffusion ModelsProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681635(3001-3009)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681635
Show More Cited By

Index Terms

StegaDDPM: Generative Image Steganography based on Denoising Diffusion Probabilistic Model
1. Information systems
  1. Information systems applications
    1. Multimedia information systems
2. Security and privacy
  1. Security services

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cover image ACM Conferences

MM '23: Proceedings of the 31st ACM International Conference on Multimedia

October 2023

9913 pages

ISBN:9798400701085

DOI:10.1145/3581783

General Chairs:
Abdulmotaleb El Saddik
University of Ottawa, Canada & MBZUAI, UAE
,
Tao Mei
HiDream.ai, China
,
Rita Cucchiara
University of Modena and Reggio Emilia, Italy
,
Program Chairs:
Marco Bertini
University of Florence, Italy
,
Diana Patricia Tobon Vallejo
Unversidad de Medellin, Colombia
,
Pradeep K. Atrey
University at Albany, State University of New York, USA
,
M. Shamim Hossain
M. Shamim Hossain (King Saud University, KSA

Copyright © 2023 ACM.

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Published: 27 October 2023

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Anhui Science and Technology Key Special Program
the Natural Science Foundation of China

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MM '23

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SIGMM

MM '23: The 31st ACM International Conference on Multimedia

October 29 - November 3, 2023

Ottawa ON, Canada

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Cited By

Hu MWang H(2025)Mutual Information-Optimized Steganalysis for Generative SteganographyIEEE Transactions on Information Forensics and Security10.1109/TIFS.2025.353908920(1852-1865)Online publication date: 2025
https://doi.org/10.1109/TIFS.2025.3539089
Ren CWu B(2024)A Robust joint coverless image steganography scheme based on two independent modulesCybersecurity10.1186/s42400-024-00299-57:1Online publication date: 7-Dec-2024
https://doi.org/10.1186/s42400-024-00299-5
Peng YWang YHu DChen KRong XZhang WCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)LDStega: Practical and Robust Generative Image Steganography based on Latent Diffusion ModelsProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681635(3001-3009)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681635
Jois TBeck GKaptchuk GLuo BLiao XXu JKirda ELie D(2024)Pulsar: Secure Steganography for Diffusion ModelsProceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security10.1145/3658644.3690218(4703-4717)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3658644.3690218
Lin KLi BLi WBarni MTondi BLiu X(2024)Constructing an Intrinsically Robust Steganalyzer via Learning Neighboring Feature Relationships and Self-Adversarial AdjustmentIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.347065119(9390-9405)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIFS.2024.3470651
Fan HZhao ZXia W(2024)Conditional Diffusion Model for Image Steganography2024 2nd International Conference on Algorithm, Image Processing and Machine Vision (AIPMV)10.1109/AIPMV62663.2024.10692262(219-224)Online publication date: 12-Jul-2024
https://doi.org/10.1109/AIPMV62663.2024.10692262
Guo YLiu Z(2024)Coverless Steganography for Face Recognition Based on Diffusion ModelIEEE Access10.1109/ACCESS.2024.347746912(148770-148782)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3477469
Yang HXu YLiu XMa X(2024)PRISEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108419133:PDOnline publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1016/j.engappai.2024.108419
Wu THu XHu YWang YLiu CZhu Y(2024)Robust Generative Steganography via Intermediate State Normal DistributionAdvanced Intelligent Computing Technology and Applications10.1007/978-981-97-5603-2_34(416-426)Online publication date: 5-Aug-2024
https://dl.acm.org/doi/10.1007/978-981-97-5603-2_34

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