Federated Transfer Learning With Client Selection for Intrusion Detection in Mobile Edge Computing
Author:
Affiliation:
1. Alibaba-NTU Singapore Joint Research Institute, Nanyang Technological University, Singapore
2. Alibaba Group, Hangzhou, China
3. School of Computer Science and Engineering, Nanyang Technological University, Singapore
Funder
Alibaba Group through Alibaba Innovative Research Program and Alibaba–NTU Singapore Joint Research Institute
NSFC
Key Project in Higher Education of Guangdong Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/4234/9731525/09668958.pdf?arnumber=9668958
Reference16 articles.
1. FedSteg: A Federated Transfer Learning Framework for Secure Image Steganalysis
2. Federated Learning With Unreliable Clients: Performance Analysis and Mechanism Design
3. Reinforcement Learning-Based Mobile Offloading for Edge Computing Against Jamming and Interference
4. Distributed Learning in Wireless Networks: Recent Progress and Future Challenges
5. Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
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