Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties

no code implementations • 28 Mar 2023 • Jingwei Sun, Zhixu Du, Anna Dai, Saleh Baghersalimi, Alireza Amirshahi, David Atienza, Yiran Chen

In this paper, we propose \textbf{Party-wise Dropout} to improve the VFL model's robustness against the unexpected exit of passive parties and a defense method called \textbf{DIMIP} to protect the active party's IP in the deployment phase.

Vertical Federated Learning