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

September 30, 2025 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Secure and Robust Watermarking for AI-generated Images: A Comprehensive Survey"

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Authors Jie Cao, Qi Li, Zelin Zhang, Jianbing Ni arXiv ID 2510.02384 Category cs.CR: Cryptography & Security Cross-listed cs.CV Citations 1 Venue arXiv.org Last Checked 4 days ago
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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