3 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CR2022★ 1 cited
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information
Xiaoyu Cao, Jinyuan Jia, Zaixi Zhang +1
Federated learning is vulnerable to poisoning attacks in which malicious clients poison the global model via sending malicious model updates to the server. Existing defenses focus…
cs.CR2022★ 1 cited
FLCert: Provably Secure Federated Learning against Poisoning Attacks
Xiaoyu Cao, Zaixi Zhang, Jinyuan Jia +1
Due to its distributed nature, federated learning is vulnerable to poisoning attacks, in which malicious clients poison the training process via manipulating their local training d…
cs.LG2021★ 3 cited
GraphMI: Extracting Private Graph Data from Graph Neural Networks
Zaixi Zhang, Qi Liu, Zhenya Huang +4
As machine learning becomes more widely used for critical applications, the need to study its implications in privacy turns to be urgent. Given access to the target model and auxil…