Introduction

Welcome to this brief AI watermarking chronology. Enjoy!

Reader note – you may also be interested in these other articles on artificial intelligence:

• A Brief Introduction To AI Model Inversion Attacks – https://briandcolwell.com/a-brief-introduction-to-ai-model-inversion-attacks/
• A Brief Introduction To AI Prompt Injection Attacks – https://briandcolwell.com/a-brief-introduction-to-ai-prompt-injection-attacks/
• A History Of AI Jailbreaking Attacks – https://briandcolwell.com/a-history-of-ai-jailbreaking-attacks/
• A History Of Clean-Label AI Data Poisoning Backdoor Attacks – https://briandcolwell.com/a-history-of-clean-label-ai-data-poisoning-attacks/
• AI Supply Chain Attacks Are A Pervasive Threat – https://briandcolwell.com/ai-supply-chain-attacks-are-a-pervasive-threat/
• An Introduction To AI Model Extraction – https://briandcolwell.com/an-introduction-to-ai-model-extraction/
• An Introduction To AI Side-Channel Attacks – https://briandcolwell.com/an-introduction-to-ai-side-channel-attacks/
• Gradient And Update Leakage (GAUL) In Federated Learning – https://briandcolwell.com/gradient-and-update-leakage-gaul-in-federated-learning/
• Membership Inference Attacks Leverage AI Model Behaviors – https://briandcolwell.com/membership-inference-attacks-leverage-ai-model-behaviors/
• What Are AI Sensitive Information Disclosure Attacks? The Threat Landscape – https://briandcolwell.com/what-are-ai-sensitive-information-disclosure-attacks/
• What Is AI Training Data Extraction? A Combination Of Techniques – https://briandcolwell.com/what-is-ai-training-data-extraction-a-combination-of-techniques/
• What Is Model Leeching? – https://briandcolwell.com/what-is-model-leeching/

AI Watermarking Development Pre-2020

• 1999: Petitcolas et al. publish early work on information hiding techniques
• 2001-2003: Atallah et al. introduce early natural language watermarking using parsed syntactic tree structures
• 2006: Topkara et al. develop ambiguity-based watermarking through synonym substitutions
• 2015: Haribabu et al. propose the first robust image watermarking model using autoencoders
• 2017: Uchida et al. introduce the first method for embedding watermarks into deep neural networks
• 2018: Zhu et al. develop HiDDeN, achieving generation of visually indistinguishable watermarked images
• 2018: Zhang et al. propose methods for protecting intellectual property of deep neural networks with watermarking
• 2018: Adi et al. introduce backdoor-based watermarking for neural networks
• 2019: Rouhani et al. develop DeepSigns, an end-to-end watermarking framework for ownership protection

AI Watermarking Development 2020-2022

• 2020: Tancik et al. introduce StegaStamp for embedding bit-string watermarks in photos
• 2021: Jia et al. propose Entangled Watermark Embedding (EWE) for defending against model extraction
• 2021: Szyller et al. introduce DAWN, a dynamic adversarial watermarking system for neural networks
• 2022: Chakraborty et al. present DynaMarks, a system for defending against deep learning model extraction

AI Watermarking Development 2023

• 2023: Kirchenbauer et al. introduce “A Watermark for Large Language Models,” a statistical approach for text watermarking
• 2023: Zhao et al. propose “A Recipe for Watermarking Diffusion Models”
• 2023: Fernandez et al. introduce Stable Signature for watermarking latent diffusion models
• 2023: Luo et al. develop CopyRNeRF for protecting copyright of Neural Radiance Fields
• 2023: Wen et al. propose Tree-Ring watermarks as fingerprints for diffusion images

AI Watermarking Development 2024

• 2024: Feng et al. introduce AquaLoRA for watermarking Stable Diffusion models
• 2024: Ci et al. develop WMAdapter for adding watermark control to latent diffusion models
• 2024: Ci et al. extend Tree-Ring to RingID for multi-key identification
• 2024: Jang et al. introduce WateRF for robust watermarking in radiance fields
• 2024: Huang et al. develop GaussianMarker for copyright protection of 3D gaussian splatting
• 2024: Zhang et al. create GS-Hider for hiding messages into 3D gaussian splatting
• 2024: Li et al. introduce GaussianStego for generative 3D gaussians splatting
• 2024: Yang et al. develop Gaussian Shading for performance-lossless image watermarking
• 2024: Lei et al. introduce DiffuseTrace, a flexible watermarking scheme for latent diffusion models
• 2024: Jiang et al. develop SmartMark for watermarking smart contracts on blockchain platforms
• 2024: Dziembowski et al. introduce VIMz for private proofs of image manipulation

AI Watermarking Development 2025

• 2025: Xu et al. develop robust multi-bit text watermarking with LLM-based paraphrasers
• 2025: Chao et al. introduce the Robust Binary Code (RBC) watermark using error-correcting codes
• 2025: Kulthe et al. create MultiNeRF for embedding multiple watermarks in Neural Radiance Fields
• 2025: Li et al. introduce GaussianSeal for 3D Gaussian Generation Model watermarking
• 2025: Petrov et al. discover watermark coexistence and develop watermark ensembling techniques
• 2025: Bagad et al. present zkDL++, a framework for cryptographic watermark verification using zero-knowledge proofs
• 2025: Sharma and Kim develop frameworks combining digital watermarking with blockchain and perceptual hash functions
• 2025: Feng et al. introduce integrated approaches combining blockchain and watermarking technologies
• 2025: Luo et al. publish a comprehensive survey on digital watermarking technology for AI-generated images

Thanks for reading!