Privacy-preserving and communication-efficient federated learning in Internet of Things

Author:

Fang ChenORCID,Guo Yuanbo,Hu Yongjin,Ma Bowen,Feng Li,Yin Anqi

Funder

PLA Information Engineering University

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference24 articles.

1. Privacy-preserving deep learning via additively homomorphic encryption;Aono;IEEE Trans. Inf. Forensics Secur.,2017

2. FedOpt: towards communication efficiency and privacy preservation in federated learning;Asad;Appl. Sci.,2020

3. Eastfly: efficient and secure ternary federated learning;Dong;Comput. Secur.,2020

4. A public key cryptosystem and a signature scheme based on discrete logarithms;ElGamal;IEEE Trans. Inf. Theory,1985

5. Highly efficient federated learning with strong privacy preservation in cloud computing;Fang;Comput. Secur.,2020

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1. A Dropout-Tolerated Privacy-Preserving Method for Decentralized Crowdsourced Federated Learning;IEEE Internet of Things Journal;2024-01-15

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4. Secure Federated Learning-Based Privacy Preserving in V2V Communications;2023 IEEE 15th International Conference on Computational Intelligence and Communication Networks (CICN);2023-12-22

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