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

• URL: http://arxiv.org/abs/2510.02384v1
• Date: Tue, 30 Sep 2025 18:59:05 GMT
• Title: Secure and Robust Watermarking for AI-generated Images: A Comprehensive Survey
• Authors: Jie Cao, Qi Li, Zelin Zhang, Jianbing Ni,
• Abstract summary: The rapid advancement of generative artificial intelligence (Gen-AI) has facilitated the effortless creation of high-quality images.<n> Watermarking has emerged as a promising solution to these challenges by distinguishing AI-generated images from natural content.<n>The survey aims to equip researchers with a holistic understanding of AI-generated image watermarking technologies.
• Score: 15.570983503312227
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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