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cs.LG2026
Understanding Backdoor Vulnerabilities in Vertical Federated Learning: The Gap Between Research and Practice
Ziqi Zhao, Jialin Lu, Junjie Shan +3
Vertical Federated Learning (VFL) enables organizations holding complementary features of shared entities to collaborate and train models. In this setting, the initiator can withho…
cs.LG2024
GDBR: Label Recovery Attack Against Partial Gradient Encryption in Federated Learning
Rui Zhang, Ka-Ho Chow
The increasing demand for data privacy, alongside the benefits of aggregating data from networked devices, has catalyzed the emergence of federated learning (FL). In FL, clients jo…
cs.LG2024
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
Junjie Shan, Ziqi Zhao, Jialin Lu +3
Foundation models that bridge vision and language have made significant progress. While they have inspired many life-enriching applications, their potential for abuse in creating n…