Black-Box Training Data Identification in GANs via Detector Networks

no code implementations • 18 Oct 2023 • Lukman Olagoke, Salil Vadhan, Seth Neel

In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if it is possible for an attacker to efficiently identify if a given point is a member of the GAN's training data.

Inference Attack Membership Inference Attack