PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining

arXiv:2311.12850v2 Announce Type: replace-cross
Abstract: Differential Privacy (DP) image data synthesis, which leverages the DP technique to generate synthetic data to replace the sensitive data, allowing organizations to share and utilize synthetic images without privacy concerns. Previous methods incorporate the advanced techniques of generative models and pre-training on a public dataset to produce exceptional DP image data, but suffer from problems of unstable training and massive computational resource demands. This paper proposes a novel DP image synthesis method, termed PRIVIMAGE, …

abstract advanced arxiv concerns cs.cr cs.cv cs.lg data differential differential privacy diffusion diffusion models generate generative generative models image image data image generation images organizations pre-training pretraining privacy semantic synthesis synthetic synthetic data training type