all InfoSec news
FedPass: Privacy-Preserving Vertical Federated Deep Learning with Adaptive Obfuscation. (arXiv:2301.12623v2 [cs.DC] UPDATED)
cs.CR updates on arXiv.org arxiv.org
Vertical federated learning (VFL) allows an active party with labeled feature
to leverage auxiliary features from the passive parties to improve model
performance. Concerns about the private feature and label leakage in both the
training and inference phases of VFL have drawn wide research attention. In
this paper, we propose a general privacy-preserving vertical federated deep
learning framework called FedPass, which leverages adaptive obfuscation to
protect the feature and label simultaneously. Strong privacy-preserving
capabilities about private features and labels are …
attention called deep learning features federated learning framework general obfuscation party performance privacy private protect research training