10 citations · 40 across the 12 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 8 cited
SAPAG: A Self-Adaptive Privacy Attack From Gradients
Yijue Wang, Jieren Deng, Dan Guo +5
Distributed learning such as federated learning or collaborative learning enables model training on decentralized data from users and only collects local gradients, where data is p…
cs.CR2020★ 6 cited
ESMFL: Efficient and Secure Models for Federated Learning
Sheng Lin, Chenghong Wang, Hongjia Li +3
Nowadays, Deep Neural Networks are widely applied to various domains. However, massive data collection required for deep neural network reveals the potential privacy issues and als…
cs.LG2020
Against Membership Inference Attack: Pruning is All You Need
Yijue Wang, Chenghong Wang, Zigeng Wang +5
The large model size, high computational operations, and vulnerability against membership inference attack (MIA) have impeded deep learning or deep neural networks (DNNs) popularit…