Secure and Privacy-Preserving Vertical Federated Learning
arXiv:2604.13474v1 Announce Type: cross
Abstract: We propose a novel end-to-end privacy-preserving framework, instantiated by three efficient protocols for different deployment scenarios, covering both input and output privacy, for the vertically spli…