623 citations · 1.1k across the 16 of their papers we have counts for
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3 papers · 1 filter
cs.CR2022★ 4 cited
Protecting Split Learning by Potential Energy Loss
Fei Zheng, Chaochao Chen, Lingjuan Lyu +5
As a practical privacy-preserving learning method, split learning has drawn much attention in academia and industry. However, its security is constantly being questioned since the…
cs.CR2020★ 7 cited
FLEAM: A Federated Learning Empowered Architecture to Mitigate DDoS in Industrial IoT
J. Li, L. Lyu, X. Liu +2
The distributed denial of service (DDoS) attack is detrimental to the industrial Internet of things (IIoT) as it triggers severe resource starvation on networked objects. Recent dy…
cs.CR2020★ 41 cited
FederBoost: Private Federated Learning for GBDT
Zhihua Tian, Rui Zhang, Xiaoyang Hou +4
Federated Learning (FL) has been an emerging trend in machine learning and artificial intelligence. It allows multiple participants to collaboratively train a better global model a…