Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models
Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models
Low-rank adaptation (LoRA) is an efficient strategy for adapting latent diffusion models (LDMs) on a training dataset to generate specific objects by minimizing the adaptation loss. However, adapted LDMs via LoRA are vulnerable to membership inference (MI) attacks that can judge whether a particular data point belongs to private training …