SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning. (arXiv:2109.12062v2 [cs.LG] UPDATED)

Privacy regulation laws, such as GDPR, impose transparency and security as
design pillars for data processing algorithms. In this context, federated
learning is one of the most influential frameworks for privacy-preserving
distributed machine learning, achieving astounding results in many natural
language processing and computer vision tasks. Several federated learning
frameworks employ differential privacy to prevent private data leakage to
unauthorized parties and malicious attackers. Many studies, however, highlight
the vulnerabilities of standard federated learning to poisoning and inference,
thus, raising …

data exchange federated learning lg