Feb. 7, 2024, 5:10 a.m. | Lei Yu Meng Han Yiming Li Changting Lin Yao Zhang Mingyang Zhang Yan Liu Haiqin Weng Y

cs.CR updates on arXiv.org arxiv.org

Vertical Federated Learning (VFL) is a federated learning paradigm where multiple participants, who share the same set of samples but hold different features, jointly train machine learning models. Although VFL enables collaborative machine learning without sharing raw data, it is still susceptible to various privacy threats. In this paper, we conduct the first comprehensive survey of the state-of-the-art in privacy attacks and defenses in VFL. We provide taxonomies for both attacks and defenses, based on their characterizations, and discuss open …

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