3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CR2025
Privacy-Preserving Federated Learning Scheme with Mitigating Model Poisoning Attacks: Vulnerabilities and Countermeasures
Jiahui Wu, Fucai Luo, Tiecheng Sun +2
The privacy-preserving federated learning schemes based on the setting of two honest-but-curious and non-colluding servers offer promising solutions in terms of security and effici…
cs.CR2023
FSSA: Efficient 3-Round Secure Aggregation for Privacy-Preserving Federated Learning
Fucai Luo, Saif Al-Kuwari, Haiyan Wang +1
Federated learning (FL) allows a large number of clients to collaboratively train machine learning (ML) models by sending only their local gradients to a central server for aggrega…
cs.CR2023★ 3 cited
ESAFL: Efficient Secure Additively Homomorphic Encryption for Cross-Silo Federated Learning
Jiahui Wu, Weizhe Zhang, Fucai Luo
Cross-silo federated learning (FL) enables multiple clients to collaboratively train a machine learning model without sharing training data, but privacy in FL remains a major chall…