Unveiling Structural Memorization: Structural Membership Inference Attack for Text-to-Image Diffusion Models

Understand

With the rapid advancements of large-scale text-to-image diffusion models, various practical applications have emerged, bringing significant convenience to society.

• However, model developers may misuse the unauthorized data to train diffusion models.
• These data are at risk of being memorized by the models, thus potentially violating citizens' privacy rights.
• Therefore, in order to judge whether a specific image is utilized as a member of a model's training set, Membership Inference Attack (MIA) is proposed to serve as a tool for privacy protection.