The rapid advancement of AI technology, particularly in generating AI-generated content (AIGC), has transformed numerous fields, e.g., art video generation, but also brings new risks, including the misuse of AI for misinformation and intellectual property theft. To address these concerns, AIGC watermarks offer an effective solution to mitigate malicious activities. However, existing watermarking surveys focus more on traditional watermarks, overlooking AIGC-specific challenges. In this work, we propose a systematic investigation into AIGC watermarking and provide the first formal definition of AIGC watermarking. Different from previous surveys, we provide a taxonomy based on the core properties of the watermark which are summarized through comprehensive literature from various AIGC modalities. Derived from the properties, we discuss the functionality and security threats of AIGC watermarking. In the end, we thoroughly investigate the AIGC governance of different countries and practitioners. We believe this taxonomy better aligns with the practical demands for watermarking in the era of GenAI, thus providing a clearer summary of existing work and uncovering potential future research directions for the community.

翻译：人工智能技术的飞速发展，特别是在生成式人工智能内容（AIGC）领域的突破，已深刻变革了艺术创作、视频生成等诸多领域，但同时也带来了新的风险，包括利用AI进行虚假信息传播和知识产权窃取。为应对这些挑战，AIGC水印技术为遏制恶意活动提供了有效解决方案。然而，现有水印综述多聚焦于传统水印方法，忽视了AIGC特有的技术难题。本研究对AIGC水印技术展开系统性探讨，首次提出AIGC水印的形式化定义。区别于既往综述，我们基于水印核心属性构建了分类体系，这些属性通过整合多模态AIGC文献得以归纳。基于该属性体系，我们深入探讨了AIGC水印的功能特性与安全威胁。最后，我们对各国及行业实践者的AIGC治理政策进行了全面调研。我们相信该分类框架能更好地契合生成式AI时代对水印技术的实际需求，从而为学界提供更清晰的研究成果总结，并揭示潜在的未来研究方向。