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

Published: September 30, 2025 | arXiv ID: 2510.02384v1

By: Jie Cao , Qi Li , Zelin Zhang and more

Potential Business Impact:

Marks AI pictures to show they're fake.

Business Areas:
Image Recognition Data and Analytics, Software

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.

Country of Origin
🇨🇦 Canada

Page Count
34 pages

Category
Computer Science:
Cryptography and Security