11 citations · 11 across the 2 of their papers we have counts for
3 papers · 1 filter
Over-the-Air Federated Learning with Enhanced Privacy
Xiaochan Xue, Moh Khalid Hasan, Shucheng Yu +2
Federated learning (FL) has emerged as a promising learning paradigm in which only local model parameters (gradients) are shared. Private user data never leaves the local devices t…
SAFELearning: Enable Backdoor Detectability In Federated Learning With Secure Aggregation
Zhuosheng Zhang, Jiarui Li, Shucheng Yu +1
For model privacy, local model parameters in federated learning shall be obfuscated before sent to the remote aggregator. This technique is referred to as \emph{secure aggregation}…
LEP-CNN: A Lightweight Edge Device Assisted Privacy-preserving CNN Inference Solution for IoT
Yifan Tian, Jiawei Yuan, Shucheng Yu +1
Supporting convolutional neural network (CNN) inference on resource-constrained IoT devices in a timely manner has been an outstanding challenge for emerging smart systems. To miti…