FedLearnSP: Preserving Privacy and Security using Federated Learning and Edge Computing-Reference-Cited by-同舟云学术

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FedLearnSP: Preserving Privacy and Security using Federated Learning and Edge Computing

Published:2021 Issue: Volume: Page:1-1
ISSN:2162-2248
Container-title:IEEE Consumer Electronics Magazine
language:
Short-container-title:IEEE Consumer Electron. Mag.

Author:

Makkar Aaisha,Ghosh Uttam,Rawat Danda B.,Abawajy Jemal

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Hardware and Architecture,Human-Computer Interaction

Link

http://xplorestaging.ieee.org/ielx7/5962380/9085929/09314266.pdf?arnumber=9314266

Cited by 29 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Quantum-empowered federated learning and 6G wireless networks for IoT security: Concept, challenges and future directions;Future Generation Computer Systems;2024-11

2. GSASG: Global Sparsification With Adaptive Aggregated Stochastic Gradients for Communication-Efficient Federated Learning;IEEE Internet of Things Journal;2024-09-01

3. A comprehensive survey of deep learning-based lightweight object detection models for edge devices;Artificial Intelligence Review;2024-08-10

4. Edge artificial intelligence for big data: a systematic review;Neural Computing and Applications;2024-04-16

5. Toward Secure and Verifiable Hybrid Federated Learning;IEEE Transactions on Information Forensics and Security;2024

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