Data to 7 Oct 2026

HiDDeN: Hiding Data With Deep Networks

arXiv 1807.09937 ↗First posted 26 Jul 2018cs.CV cs.LGcited by 384

Not on the map. Why?

Cited by 134 in LLM safety and security, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Recent work has shown that deep neural networks are highly sensitive to tiny perturbations of input images, giving rise to adversarial examples. Though this property is usually considered a weakness of learned models, we explore whether it can be beneficial. We find that neural networks can learn to use invisible perturbations to encode a rich amount of useful information. In fact, one can exploit this capability for the task of data hiding. We jointly train encoder and decoder networks, where given an input message and cover image, the encoder produces a visually indistinguishable encoded image, from which the decoder can recover the original message. We show that these encodings are competitive with existing data hiding algorithms, and further that they can be made robust to noise: our models learn to reconstruct hidden information in an encoded image despite the presence of Gaussian blurring, pixel-wise dropout, cropping, and JPEG compression. Even though JPEG is non-differentiable, we show that a robust model can be trained using differentiable approximations. Finally, we demonstrate that adversarial training improves the visual quality of encoded images.

Key facts. Cited by 384 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Jul 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 30; 2022: 24; 2023: 53; 2024: 92; 2025: 100; 2026: 85.

384 papers.

Sort:

By area:

2023A Watermark for Large Language Modelscited by 667
2024Moshi: a speech-text foundation model for real-time dialoguecited by 536
2023The Stable Signature: Rooting Watermarks in Latent Diffusion Modelscited by 289
2023Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robustcited by 179
2022A Self-Supervised Descriptor for Image Copy Detectioncited by 175
2024Gaussian Shading: Provable Performance-Lossless Image Watermarking for Diffusion Modelscited by 131
2023Invisible Image Watermarks Are Provably Removable Using Generative AIcited by 124
2023EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protectioncited by 109
2021MBRS : Enhancing Robustness of DNN-based Watermarking by Mini-Batch of Real and Simulated JPEG Compressioncited by 108
2024Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advancescited by 105
2021Watermarking Images in Self-Supervised Latent Spacescited by 90
2024WAVES: Benchmarking the Robustness of Image Watermarkscited by 89

38 more

2024RingID: Rethinking Tree-Ring Watermarking for Enhanced Multi-Key Identificationcited by 87
2023Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Modelscited by 77
2023Robust Multi-bit Natural Language Watermarking through Invariant Featurescited by 76
2023Evading Watermark based Detection of AI-Generated Contentcited by 74
2022Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanismscited by 61
2023RoSteALS: Robust Steganography using Autoencoder Latent Spacecited by 54
2023WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Modelscited by 51
2023Advancing Beyond Identification: Multi-bit Watermark for Large Language Modelscited by 51
2021Poison Ink: Robust and Invisible Backdoor Attackcited by 50
2023CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganographycited by 50
2023TrustMark: Universal Watermarking for Arbitrary Resolution Imagescited by 50
2024Watermark Anything with Localized Messagescited by 49
2024Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Modelscited by 48
2021Deep Model Intellectual Property Protection via Deep Watermarkingcited by 47
2021Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attackcited by 45
2024ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimizationcited by 45
2024Video Seal: Open and Efficient Video Watermarkingcited by 45
2023SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake Detectioncited by 43
2024Image Watermarks are Removable Using Controllable Regeneration from Clean Noisecited by 43
2024SoK: Watermarking for AI-Generated Contentcited by 43
2024AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRAcited by 42
2023DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Modelscited by 41
2024Diffusion Facial Forgery Detectioncited by 41
2021Tracing Text Provenance via Context-Aware Lexical Substitutioncited by 40
2022Supervised GAN Watermarking for Intellectual Property Protectioncited by 39
2025GeometryCrafter: Consistent Geometry Estimation for Open-world Videos with Diffusion Priorscited by 36
2022Proactive Image Manipulation Detectioncited by 35
2024Copyright Protection in Generative AI: A Technical Perspectivecited by 35
2024OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarkingcited by 35
2024A Watermark-Conditioned Diffusion Model for IP Protectioncited by 34
2023CopyRNeRF: Protecting the CopyRight of Neural Radiance Fieldscited by 33
2024Attack-Resilient Image Watermarking Using Stable Diffusioncited by 33
2024WMAdapter: Adding WaterMark Control to Latent Diffusion Modelscited by 29
2024V2A-Mark: Versatile Deep Visual-Audio Watermarking for Manipulation Localization and Copyright Protectioncited by 27
2024LaWa: Using Latent Space for In-Generation Image Watermarkingcited by 27
2024A Transfer Attack to Image Watermarkscited by 26
2024GS-Hider: Hiding Messages into 3D Gaussian Splattingcited by 26
2024SleeperMark: Towards Robust Watermark against Fine-Tuning Text-to-image Diffusion Modelscited by 26

50 most cited of 384 All 384 (JSON)