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Membership Inference Attacks against Diffusion Models. (arXiv:2302.03262v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
Diffusion models have attracted attention in recent years as innovative
generative models. In this paper, we investigate whether a diffusion model is
resistant to a membership inference attack, which evaluates the privacy leakage
of a machine learning model. We primarily discuss the diffusion model from the
standpoints of comparison with a generative adversarial network (GAN) as
conventional models and hyperparameters unique to the diffusion model, i.e.,
time steps, sampling steps, and sampling variances. We conduct extensive
experiments with DDIM as …
adversarial attack attacks attention diffusion models discuss gan generative machine machine learning network privacy