Yonghao Zhang1,3, Yongtang Wu2, Tao Li1, Hui Zhou1,3, Yuling Chen1,2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 345-361, 2023, DOI:10.32604/cmes.2023.026920
Abstract The data in Mobile Edge Computing (MEC) contains tremendous market value, and data sharing can maximize the
usefulness of the data. However, certain data is quite sensitive, and sharing it directly may violate privacy. Vertical
Federated Learning (VFL) is a secure distributed machine learning framework that completes joint model training
by passing encrypted model parameters rather than raw data, so there is no data privacy leakage during the training
process. Therefore, the VFL can build a bridge between data demander and owner to realize data sharing while
protecting data privacy. Typically, the VFL requires a third party for key distribution… More >
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