mlsanityData to 14 Oct 2026

Fantastyc: Blockchain-based Federated Learning Made Secure and Practical

arXiv 2406.03608 ↗First posted 5 Jun 2024cs.CR cs.DCcited by 2

Not on the map. Why?

Abstract (arXiv)

Federated Learning is a decentralized framework that enables multiple clients to collaboratively train a machine learning model under the orchestration of a central server without sharing their local data. The centrality of this framework represents a point of failure which is addressed in literature by blockchain-based federated learning approaches. While ensuring a fully-decentralized solution with traceability, such approaches still face several challenges about integrity, confidentiality and scalability to be practically deployed. In this paper, we propose Fantastyc, a solution designed to address these challenges that have been never met together in the state of the art.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Jun 2024.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2025: 2.

2 papers.