Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning

no code implementations • 25 May 2020 • Renuga Kanagavelu, Zengxiang Li, Juniarto Samsudin, Yechao Yang, Feng Yang, Rick Siow Mong Goh, Mervyn Cheah, Praewpiraya Wiwatphonthana, Khajonpong Akkarajitsakul, Shangguang Wangz

Countries across the globe have been pushing strict regulations on the protection of personal or private data collected.

Distributed, Parallel, and Cluster Computing

Privacy-preserving Weighted Federated Learning within Oracle-Aided MPC Framework

no code implementations • 17 Mar 2020 • Huafei Zhu, Zengxiang Li, Mervyn Cheah, Rick Siow Mong Goh

In the second fold, an oracle-aided MPC solution for computing weighted federated learning is formalized by decoupling the security of federated learning systems from that of underlying multi-party computations.

Cryptography and Security