Secure and Efficient Federated Learning in LEO Constellations Using Decentralized Key Generation and On-Orbit Model Aggregation
Author:
Affiliation:
1. Missouri University of Science and Technology,Computer Science Department,Rolla,MO,USA,65401
2. School of Computer and Cyber Sciences, Augusta University,Augusta,GA,USA,30912
Funder
National Science Foundation (NSF)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10436708/10436716/10436841.pdf?arnumber=10436841
Reference17 articles.
1. Communication-efficient learning of deep networks from decentralized data;McMahan;AISTATS,2017
2. Satellite-Based Computing Networks with Federated Learning
3. Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
4. On-Board Federated Learning for Dense LEO Constellations
5. Optimizing Federated Learning in LEO Satellite Constellations via Intra-Plane Model Propagation and Sink Satellite Scheduling
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4. Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning;2024 IEEE International Conference on Pervasive Computing and Communications (PerCom);2024-03-11
5. FedSafe-No KDC Needed: Decentralized Federated Learning with Enhanced Security and Efficiency;2024 IEEE 21st Consumer Communications & Networking Conference (CCNC);2024-01-06
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