Towards robust and privacy-preserving federated learning in edge computing

Hongliang Zhou; Yifeng Zheng; Xiaohua Jia

doi:10.1016/j.comnet.2024.110321

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JOURNAL ARTICLE

Towards robust and privacy-preserving federated learning in edge computing

Hongliang Zhou Yifeng Zheng Xiaohua Jia

Year: 2024 Journal: Computer Networks Vol: 243 Pages: 110321-110321 Publisher: Elsevier BV

DOI: 10.1016/j.comnet.2024.110321

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Keywords:

Computer science Differential privacy Federated learning Robustness (evolution) Computer security Edge computing Information privacy Salient Edge device Enhanced Data Rates for GSM Evolution Artificial intelligence Machine learning Data mining Cloud computing

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Privacy-Preserving Technologies in Data

Physical Sciences → Computer Science → Artificial Intelligence

Cryptography and Data Security

Physical Sciences → Computer Science → Artificial Intelligence

Mobile Crowdsensing and Crowdsourcing

Physical Sciences → Computer Science → Computer Science Applications

Towards robust and privacy-preserving federated learning in edge computing

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