Heng Swee Huay

PryML: Privacy-Preserving Federated Learning under Data Heterogeneity using CKKS Encryption

Federated Learning enables collaborative model training across distributed clients without centralizing raw data, offering privacy advantages for sensitive domains such as healthcare and finance. However, recent work has shown that standard federated protocols remain vulnerable to gradient inversion attacks, where a ma...