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, …

advanced arxiv aware cs.cr cs.cv cs.lg data differential privacy diffusion models generative generative models image image generation images organizations privacy privacy concerns private semantic sensitive sensitive data share synthetic synthetic data techniques training