631 citations · 2.1k across the 14 of their papers we have counts for
5 papers · 1 filter
Backdoor attacks and defenses in feature-partitioned collaborative learning
Yang Liu, Zhihao Yi, Tianjian Chen
Since there are multiple parties in collaborative learning, malicious parties might manipulate the learning process for their own purposes through backdoor attacks. However, most o…
Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
Ce Ju, Ruihui Zhao, Jichao Sun +11
Prevention of stroke with its associated risk factors has been one of the public health priorities worldwide. Emerging artificial intelligence technology is being increasingly adop…
Learning to Detect Malicious Clients for Robust Federated Learning
Suyi Li, Yong Cheng, Wei Wang +2
Federated learning systems are vulnerable to attacks from malicious clients. As the central server in the system cannot govern the behaviors of the clients, a rogue client may init…
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning
Yang Liu, Anbu Huang, Yun Luo +7
Visual object detection is a computer vision-based artificial intelligence (AI) technique which has many practical applications (e.g., fire hazard monitoring). However, due to priv…
RPN: A Residual Pooling Network for Efficient Federated Learning
Anbu Huang, Yuanyuan Chen, Yang Liu +2
Federated learning is a distributed machine learning framework which enables different parties to collaboratively train a model while protecting data privacy and security. Due to m…