mlsanityData to 7 Oct 2026

Stable Messenger: Steganography for Message-Concealed Image Generation

arXiv 2312.01284 ↗First posted 3 Dec 2023cs.CVcited by 2

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Abstract (arXiv)

In the ever-expanding digital landscape, safeguarding sensitive information remains paramount. This paper delves deep into digital protection, specifically focusing on steganography. While prior research predominantly fixated on individual bit decoding, we address this limitation by introducing ``message accuracy'', a novel metric evaluating the entirety of decoded messages for a more holistic evaluation. In addition, we propose an adaptive universal loss tailored to enhance message accuracy, named Log-Sum-Exponential (LSE) loss, thereby significantly improving the message accuracy of recent approaches. Furthermore, we also introduce a new latent-aware encoding technique in our framework named Approach, harnessing pretrained Stable Diffusion for advanced steganographic image generation, giving rise to a better trade-off between image quality and message recovery. Throughout experimental results, we have demonstrated the superior performance of the new LSE loss and latent-aware encoding technique. This comprehensive approach marks a significant step in evolving evaluation metrics, refining loss functions, and innovating image concealment techniques, aiming for more robust and dependable information protection.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 17 of its 41 references that are in the map. First posted on arXiv 3 Dec 2023.

Builds on

17 of 41 references.

References · 17

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  3. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  4. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  5. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  6. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  7. 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
  8. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 921
  9. 2023Muse: Text-To-Image Generation via Masked Generative Transformerscited by 640
  10. 2018HiDDeN: Hiding Data With Deep Networkscited by 384
  11. 2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 289
  12. 2019StegaStamp: Invisible Hyperlinks in Physical Photographscited by 256
5 more
  1. 2019Robust Invisible Video Watermarking with Attentioncited by 144
  2. 2023RoSteALS: Robust Steganography using Autoencoder Latent Spacecited by 54
  3. 2023WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Modelscited by 51
  4. 2023Generative Watermarking Against Unauthorized Subject-Driven Image Synthesiscited by 21
  5. 2022Image data hiding with multi-scale autoencoder networkcited by 3

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Citing papers per year: 2024: 2.

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  1. 2026Feedback Coding Enables Inference-Time Covert Agentic Communication ↗
  2. 2025CIF: A Constrained Inversion Framework for Reliable Message Extraction in Diffusion-Based Generative Steganography
  3. 2024Plug-and-Hide: Provable and Adjustable Diffusion Generative Steganography
  4. 2025Provably Secure Covert Messaging Using Image-based Diffusion Processes
  5. 2026Synchronized Logit Steering: Real-world Steganography
  6. 2025Shackled Dancing: A Bit-Locked Diffusion Algorithm for Lossless and Controllable Image Steganography
  7. 2026DTAMS: High-Capacity Generative Steganography via Dynamic Multi-Timestep Selection and Adaptive Deviation Mapping in Latent Diffusion
  8. 2024Diffusion-Based Hierarchical Image Steganography