mlsanityData to 7 Oct 2026

GFL: A Decentralized Federated Learning Framework Based On Blockchain

arXiv 2010.10996 ↗First posted 21 Oct 2020cs.LG cs.CR cs.DCcited by 12

Not on the map. Why?

Abstract (arXiv)

Federated learning(FL) is a rapidly growing field and many centralized and decentralized FL frameworks have been proposed. However, it is of great challenge for current FL frameworks to improve communication performance and maintain the security and robustness under malicious node attacks. In this paper, we propose Galaxy Federated Learning Framework(GFL), a decentralized FL framework based on blockchain. GFL introduces the consistent hashing algorithm to improve communication performance and proposes a novel ring decentralized FL algorithm(RDFL) to improve decentralized FL performance and bandwidth utilization. In addition, GFL introduces InterPlanetary File System(IPFS) and blockchain to further improve communication efficiency and FL security. Our experiments show that GFL improves communication performance and decentralized FL performance under the data poisoning of malicious nodes and non-independent and identically distributed(Non-IID) datasets.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Oct 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 2; 2023: 3; 2024: 2; 2025: 1; 2026: 1.

12 papers.

  1. 2023A Survey on Decentralized Federated Learningcited by 27
  2. 2021A Decentralized Federated Learning Framework via Committee Mechanism with Convergence Guaranteecited by 16
  3. 2022Federated Learning Attacks and Defenses: A Surveycited by 11
  4. 2023P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setupscited by 3
  5. 2021Reward-Based 1-bit Compressed Federated Distillation on Blockchaincited by 2
  6. 2022Analyzing the Robustness of Decentralized Horizontal and Vertical Federated Learning Architectures in a Non-IID Scenariocited by 2
  7. 2021Federated Learning for Cross-block Oil-water Layer Identificationcited by 0
  8. 2023A Comprehensive Empirical Study of Bugs in Open-Source Federated Learning Frameworkscited by 0
  9. 2024Federated Computing -- Survey on Building Blocks, Extensions and Systemscited by 0
  10. 2024CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Communitycited by 0
  11. 2025MAR-FL: A Communication Efficient Peer-to-Peer Federated Learning Systemcited by 0
  12. 2026PenTiDef: Decentralized Federated Intrusion Detection System with Differential Privacy and Latent-Space Defense via Blockchain Coordination in IIoTcited by 0