33 citations · 147 across the 38 of their papers we have counts for
8 papers · 1 filter
FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders
Hanlin Gu, Lixin Fan, Xingxing Tang +1
This paper proposes a general spectral analysis framework that thwarts a security risk in federated Learning caused by groups of malicious Byzantine attackers or colluders, who con…
FedTracker: Furnishing Ownership Verification and Traceability for Federated Learning Model
Shuo Shao, Wenyuan Yang, Hanlin Gu +4
Federated learning (FL) is a distributed machine learning paradigm allowing multiple clients to collaboratively train a global model without sharing their local data. However, FL e…
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
Yan Kang, Jiahuan Luo, Yuanqin He +3
Federated learning (FL) has emerged as a practical solution to tackle data silo issues without compromising user privacy. One of its variants, vertical federated learning (VFL), ha…
Trading Off Privacy, Utility and Efficiency in Federated Learning
Xiaojin Zhang, Yan Kang, Kai Chen +2
Federated learning (FL) enables participating parties to collaboratively build a global model with boosted utility without disclosing private data information. Appropriate protecti…
A Hybrid Self-Supervised Learning Framework for Vertical Federated Learning
Yuanqin He, Yan Kang, Xinyuan Zhao +4
Vertical federated learning (VFL), a variant of Federated Learning (FL), has recently drawn increasing attention as the VFL matches the enterprises' demands of leveraging more valu…
Accelerating Vertical Federated Learning
Dongqi Cai, Tao Fan, Yan Kang +4
Privacy, security and data governance constraints rule out a brute force process in the integration of cross-silo data, which inherits the development of the Internet of Things. Fe…
Federated Learning with Quantum Secure Aggregation
Yichi Zhang, Chao Zhang, Cai Zhang +3
This article illustrates a novel Quantum Secure Aggregation (QSA) scheme that is designed to provide highly secure and efficient aggregation of local model parameters for federated…
FadMan: Federated Anomaly Detection across Multiple Attributed Networks
Nannan Wu, Ning Zhang, Wenjun Wang +2
Anomaly subgraph detection has been widely used in various applications, ranging from cyber attack in computer networks to malicious activities in social networks. Despite an incre…