Does Label Differential Privacy Prevent Label Inference Attacks?
Analyzes the effectiveness of label-DP in mitigating label inference attacks and provides insights on privacy settings and attack bounds.
Label Inference Attack
Defending Batch-Level Label Inference and Replacement Attacks in Vertical Federated Learning
Explores vulnerabilities in VFL models to label inference and backdoor attacks and proposes effective defenses like CAE and DCAE.
Label Inference Attacks Against Vertical Federated Learning
Evaluates privacy risks of vertical federated learning (VFL) and proposes label inference attacks with outstanding performance, highlighting vulnerabilities and defense limitations.