Robust and privacy-preserving federated learning with distributed additive encryption against poisoning attacks

Author:

Zhang Fan,Huang HuiORCID,Chen Zhixiong,Huang Zhenjie

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference48 articles.

1. Communication-efficient learning of deep networks from decentralized data;McMahan,2017

2. BAYHENN: Combining Bayesian deep learning and homomorphic encryption for secure DNN inference;Xie,2019

3. Homomorphic encryption-based privacy-preserving federated learning in iot-enabled healthcare system;Zhang;IEEE Trans. Netw. Sci. Eng.,2022

4. Federated learning for wireless communications: Motivation, opportunities, and challenges;Niknam;IEEE Commun. Mag.,2020

5. Analyzing federated learning through an adversarial lens;Bhagoji,2019

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