Falkor: Federated Learning Secure Aggregation Powered by AES-CTR GPU Implementation

ePrint Report: Falkor: Federated Learning Secure Aggregation Powered by AES-CTR GPU Implementation

Mariya Georgieva Belorgey, Sofia Dandjee, Nicolas Gama, Dimitar Jetchev, Dmitry Mikushin

We propose a novel protocol, Falkor, for secure aggregation for Federated Learning in the multi-server scenario based on masking of local models via a stream cipher based on AES in counter mode and accelerated by GPUs running on the aggregating servers. The protocol is resilient to client dropout and has reduced clients/servers communication cost by a factor …

aes aggregation cipher ctr eprint report federated learning gpu implementation local masking novel protocol report scenario server stream stream cipher