Secure and Robust Watermarking for AI-generated Images: A Comprehensive Survey

Jie Cao, Qi Li, Zelin Zhang, Jianbing Ni
9/30/2025
cs.CRcs.CV

No confident code implementation found for this paper. 3 possible matches can be shown below.

Abstract

The rapid advancement of generative artificial intelligence (Gen-AI) has facilitated the effortless creation of high-quality images, while simultaneously raising critical concerns regarding intellectual property protection, authenticity, and accountability. Watermarking has emerged as a promising solution to these challenges by distinguishing AI-generated images from natural content, ensuring provenance, and fostering trustworthy digital ecosystems. This paper presents a comprehensive survey of the current state of AI-generated image watermarking, addressing five key dimensions: (1) formalization of image watermarking systems; (2) an overview and comparison of diverse watermarking techniques; (3) evaluation methodologies with respect to visual quality, capacity, and detectability; (4) vulnerabilities to malicious attacks; and (5) prevailing challenges and future directions. The survey aims to equip researchers with a holistic understanding of AI-generated image watermarking technologies, thereby promoting their continued development.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

TraceMark-LDM: Authenticatable Watermarking for Latent Diffusion Models via Binary-Guided Rearrangement

87% match2025

LaWa: Using Latent Space for In-Generation Image Watermarking

87% match1 repo182026

Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks

86% match1 repo402026

Transferable Black-Box One-Shot Forging of Watermarks via Image Preference Models

85% match2025

MetaSeal: Defending Against Image Attribution Forgery Through Content-Dependent Cryptographic Watermarks

85% match1 repo12025

SoK: Watermarking for AI-Generated Content

85% match2024

Cite this paper

@article{cao2025secure,
  title  = {Secure and Robust Watermarking for AI-generated Images: A Comprehensive Survey},
  author = {Jie Cao and Qi Li and Zelin Zhang and Jianbing Ni},
  year   = {2025},
  eprint = {2510.02384},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.02384v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2510.02384.svg)](https://codeofpaper.com/paper/2510.02384)

Discussion