4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CR2024
TBDD: A New Trust-based, DRL-driven Framework for Blockchain Sharding in IoT
Zixu Zhang, Guangsheng Yu, Caijun Sun +7
Integrating sharded blockchain with IoT presents a solution for trust issues and optimized data flow. Sharding boosts blockchain scalability by dividing its nodes into parallel sha…
cs.LG2023★ 3 cited
A Secure Aggregation for Federated Learning on Long-Tailed Data
Yanna Jiang, Baihe Ma, Xu Wang +4
As a distributed learning, Federated Learning (FL) faces two challenges: the unbalanced distribution of training data among participants, and the model attack by Byzantine nodes. I…
cs.LG2023★ 4 cited
IronForge: An Open, Secure, Fair, Decentralized Federated Learning
Guangsheng Yu, Xu Wang, Caijun Sun +5
Federated learning (FL) provides an effective machine learning (ML) architecture to protect data privacy in a distributed manner. However, the inevitable network asynchrony, the ov…