Protecting Against Unauthorized Dataset Use in Fine-Tuning Text-to-Image Diffusion Models

Text-to-image AI models like Stable Diffusion can create realistic images but their training datasets risk being used without permission, which violates the rights of data owners. Researchers propose a dataset watermarking framework (a technique that embeds hidden markers into data to track and detect unauthorized use) that can detect when datasets are misused during fine-tuning (the process of adapting a pre-trained AI model to a specific task) while keeping the images high-quality and usable. The framework was tested on Stable Diffusion and showed it can reliably identify and trace dataset misuse with minimal changes to the original data.