Advancing Security and Efficiency in Federated Learning Service Aggregation for Wireless Networks
Author:
Affiliation:
1. École de Technologie Supérieure (ÉTS),Resilient Machine Learning Institute (ReMI),Montréal,Canada
Funder
Mitacs
Natural Sciences and Engineering Research Council of Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10293227/10293746/10293790.pdf?arnumber=10293790
Reference23 articles.
1. A Hybrid Approach to Privacy-Preserving Federated Learning;stacey;Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security,0
2. Cost-efficient Federated Reinforcement Learning- Based Network Routing for Wireless Networks
3. Malicious Node Detection Using Machine Learning and Distributed Data Storage Using Blockchain in WSNs
4. Privacy-Preserving Federated Learning for Value-Added Service Model in Advanced Metering Infrastructure
5. Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization
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