Engineering Commons^™

A New Implementation Of Federated Learning For Privacy And Security Enhancement, Xiang Ma, Haijian Sun, Rose Qingyang Hu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications

Motivated by the ever-increasing concerns on personal data privacy and the rapidly growing data volume at local clients, federated learning (FL) has emerged as a new machine learning setting. An FL system is comprised of a central parameter server and multiple local clients. It keeps data at local clients and learns a centralized model by sharing the model parameters learned locally. No local data needs to be shared, and privacy can be well protected. Nevertheless, since it is the model instead of the raw data that is shared, the system can be exposed to the poisoning model attacks launched by …