The personalization techniques of diffusion models succeed in generating specific concepts but also pose threats to copyright protection and illegal use. Model Watermarking is an effective method to prevent the unauthorized use of subject-driven or style-driven image generation, safeguarding concept copyrights. However, under the goal of concept-oriented protection, current watermarking schemes typically add watermarks to all images rather than applying them in a refined manner targeted at specific concepts. Additionally, the personalization techniques of diffusion models can easily remove watermarks. Existing watermarking methods struggle to achieve fine-grained watermark embedding with a few images of specific concept and prevent removal of watermarks through personalized fine-tuning. Therefore, we introduce a novel concept-oriented watermarking framework that seamlessly embeds imperceptible watermarks into the concept of diffusion models. We conduct extensive experiments and ablation studies to verify our framework. Our code is available at https://anonymous.4open.science/r/Conceptwm-4EB3/.

翻译：扩散模型的个性化技术虽然能够成功生成特定概念，但也对版权保护和非法使用构成了威胁。模型水印是防止未经授权使用主体驱动或风格驱动的图像生成、保护概念版权的有效方法。然而，在面向概念保护的目标下，当前的水印方案通常对所有图像添加水印，而非针对特定概念进行精细化应用。此外，扩散模型的个性化技术可以轻易去除水印。现有的水印方法难以利用特定概念的少量图像实现细粒度的水印嵌入，也无法防止通过个性化微调去除水印。因此，我们提出了一种新颖的面向概念的水印框架，能够将不可感知的水印无缝嵌入到扩散模型的概念中。我们进行了广泛的实验和消融研究以验证我们的框架。我们的代码可在 https://anonymous.4open.science/r/Conceptwm-4EB3/ 获取。