mlsanityData to 7 Oct 2026

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

arXiv 2107.09287 ↗First posted 20 Jul 2021cs.CVcited by 23

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Abstract (arXiv)

The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding. By embedding information into a noise-tolerant signal such as audio, video, or images, digital watermarking and steganography techniques can be used to protect sensitive intellectual property and enable confidential communication, ensuring that the information embedded is only accessible to authorized parties. This survey provides an overview of recent developments in deep learning techniques deployed for data hiding, categorized systematically according to model architectures and noise injection methods. The objective functions, evaluation metrics, and datasets used for training these data hiding models are comprehensively summarised. Additionally, potential future research directions that unite digital watermarking and steganography on software engineering to enhance security and mitigate risks are suggested and deliberated. This contribution furthers the creation of a more trustworthy digital world and advances Responsible AI.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 44 of its 104 references that are in the map. First posted on arXiv 20 Jul 2021.

Builds on

44 of 104 references.

References · 44

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32 more
  1. 2018HiDDeN: Hiding Data With Deep Networkscited by 384
  2. 2019StegaStamp: Invisible Hyperlinks in Physical Photographscited by 256
  3. 2019Robust Invisible Video Watermarking with Attentioncited by 144
  4. 2020Entangled Watermarks as a Defense against Model Extractioncited by 144
  5. 2020Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hidingcited by 121
  6. 2020Distortion Agnostic Deep Watermarkingcited by 88
  7. 2021Hidden Backdoors in Human-Centric Language Modelscited by 83
  8. 2019SteganoGAN: High Capacity Image Steganography with GANscited by 70
  9. 2020A Comprehensive Survey on Deep Music Generation: Multi-level Representations, Algorithms, Evaluations, and Future Directionscited by 56
  10. 2018ReDMark: Framework for Residual Diffusion Watermarking on Deep Networkscited by 55
  11. 2019Generating Sentiment-Preserving Fake Online Reviews Using Neural Language Models and Their Human- and Machine-based Detectioncited by 50
  12. 2021DVMark: A Deep Multiscale Framework for Video Watermarkingcited by 42
  13. 2019REFIT: A Unified Watermark Removal Framework For Deep Learning Systems With Limited Datacited by 40
  14. 2014StegExpose - A Tool for Detecting LSB Steganographycited by 25
  15. 2021Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderingscited by 23
  16. 2018CNN Based Adversarial Embedding with Minimum Alteration for Image Steganographycited by 22
  17. 2017Steganographic Generative Adversarial Networkscited by 21
  18. 2018Invisible Steganography via Generative Adversarial Networkscited by 21
  19. 2017End-to-end Trained CNN Encode-Decoder Networks for Image Steganographycited by 18
  20. 2019ROMark: A Robust Watermarking System Using Adversarial Trainingcited by 17
  21. 2018DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Modelscited by 16
  22. 2018StegNet: Mega Image Steganography Capacity with Deep Convolutional Networkcited by 14
  23. 2020Unconditional Audio Generation with Generative Adversarial Networks and Cycle Regularizationcited by 12
  24. 2017A Robust Blind Watermarking Using Convolutional Neural Networkcited by 11
  25. 2021A Brief Survey on Deep Learning Based Data Hidingcited by 9
  26. 2020Robust Spatial-spread Deep Neural Image Watermarkingcited by 6
  27. 2019A Robust Image Watermarking System Based on Deep Neural Networkscited by 5
  28. 2020Robust Data Hiding Using Inverse Gradient Attentioncited by 5
  29. 2017Deep Learning-Based Dynamic Watermarking for Secure Signal Authentication in the Internet of Thingscited by 4
  30. 2019Hiding Data in Images Using Cryptography and Deep Neural Networkcited by 4
  31. 2018Paired 3D Model Generation with Conditional Generative Adversarial Networkscited by 3
  32. 2020Robust watermarking with double detector-discriminator approachcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 1; 2023: 3; 2024: 6; 2025: 8; 2026: 3.

23 papers.

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  1. 2021Watermarking Images in Self-Supervised Latent Spacescited by 90
  2. 2024Visibility into AI Agentscited by 77
  3. 2025Authenticated Delegation and Authorized AI Agentscited by 63
  4. 2022Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanismscited by 61
  5. 2024IDs for AI Systemscited by 18
  6. 2023Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyondcited by 14
  7. 2024Generative AI for the Optimization of Next-Generation Wireless Networks: Basics, State-of-the-Art, and Open Challengescited by 14
  8. 2025The NeRF Signature: Codebook-Aided Watermarking for Neural Radiance Fieldscited by 10
  9. 2021A Compact Neural Network-based Algorithm for Robust Image Watermarkingcited by 6
  10. 2025Re-Key-Free, Risky-Free: Adaptable Model Usage Controlcited by 6
  11. 2023PRIS: Practical robust invertible network for image steganographycited by 5
  12. 2026Tool Use Enables Undetectable Steganography in Multi-Agent LLM Systemscited by 5
11 more
  1. 2023A Brief Yet In-Depth Survey of Deep Learning-Based Image Watermarkingcited by 2
  2. 2024Finding needles in a haystack: A Black-Box Approach to Invisible Watermark Detectioncited by 2
  3. 2026SIGMark: Scalable In-Generation Watermark with Blind Extraction for Video Diffusioncited by 2
  4. 2024Picking watermarks from noise (PWFN): an improved robust watermarking model against intensive distortionscited by 1
  5. 2025Fragile Watermarking for Image Certification Using Deep Steganographic Embeddingcited by 1
  6. 2024Model X-Ray: Detection of Hidden Malware in AI Model Weights using Few Shot Learningcited by 0
  7. 2025Steganographic Embeddings as an Effective Data Augmentationcited by 0
  8. 2025Slice or the Whole Pie? Utility Control for AI Modelscited by 0
  9. 2025Deep Data Hiding for ICAO-Compliant Face Images: A Surveycited by 0
  10. 2025Foveation Improves Payload Capacity in Steganographycited by 0
  11. 2026A Training-Free Proactive Defense Against Partial Speech Manipulation via Self-Embedding Steganographycited by 0