14 citations · 20 across the 5 of their papers we have counts for
5 papers
DeDe: Detecting Backdoor Samples for SSL Encoders via Decoders
Sizai Hou, Songze Li, Duanyi Yao
Self-supervised learning (SSL) is pervasively exploited in training high-quality upstream encoders with a large amount of unlabeled data. However, it is found to be susceptible to…
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit
Duanyi Yao, Songze Li, Ye Xue +1
Vertical federated learning (VFL), where each participating client holds a subset of data features, has found numerous applications in finance, healthcare, and IoT systems. However…
HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning
Zhuoning Guo, Duanyi Yao, Qiang Yang +1
Federated Graph Learning (FGL) has emerged as a promising way to learn high-quality representations from distributed graph data with privacy preservation. Despite considerable effo…
URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning
Duanyi Yao, Songze Li, Xueluan Gong +2
Launching effective malicious attacks in VFL presents unique challenges: 1) Firstly, given the distributed nature of clients' data features and models, each client rigorously guard…
FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models
Songze Li, Duanyi Yao, Jin Liu
In a vertical federated learning (VFL) system consisting of a central server and many distributed clients, the training data are vertically partitioned such that different features…