3 papers
cs.CV2024
MGIC: A Multi-Label Gradient Inversion Attack based on Canny Edge Detection on Federated Learning
Can Liu, Jin Wang
As a new distributed computing framework that can protect data privacy, federated learning (FL) has attracted more and more attention in recent years. It receives gradients from us…
cs.CV2024
AFGI: Towards Accurate and Fast-convergent Gradient Inversion Attack in Federated Learning
Can Liu, Jin Wang, and Yipeng Zhou +3
Federated learning (FL) empowers privacypreservation in model training by only exposing users' model gradients. Yet, FL users are susceptible to gradient inversion attacks (GIAs) w…
cs.CR2023
RecAGT: Shard Testable Codes with Adaptive Group Testing for Malicious Nodes Identification in Sharding Permissioned Blockchain
Dong-Yang Yu, Jin Wang, Lingzhi Li +2
Recently, permissioned blockchain has been extensively explored in various fields, such as asset management, supply chain, healthcare, and many others. Many scholars are dedicated…