  In this work, we review the architecture design of existing federated General
Adversarial Networks (GAN) solutions and highlight the security and
trust-related weaknesses in the existing designs. We then describe how these
weaknesses make existing designs unsuitable for the requirements needed for a
consortium of health registries working towards generating synthetic datasets
for research purposes. Moreover, we propose how these weaknesses can be
addressed with our novel architecture solution. Our novel architecture solution
combines several building blocks to generate synthetic data in a decentralised
setting. Consortium blockchains, secure multi-party computations, and
homomorphic encryption are the core building blocks of our proposed
architecture solution to address the weaknesses in the existing design of
federated GANs. Finally, we discuss our proposed solution's advantages and
future research directions.
