3 papers
cs.CR2024
Fantastyc: Blockchain-based Federated Learning Made Secure and Practical
William Boitier, Antonella Del Pozzo, Álvaro García-Pérez +9
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…
cs.DC2020
Leaderless State-Machine Replication: Specification, Properties, Limits (Extended Version)
Tuanir França Rezende, Pierre Sutra
Modern Internet services commonly replicate critical data across several geographical locations using state-machine replication (SMR). Due to their reliance on a leader replica, cl…
cs.DC2020
State-Machine Replication for Planet-Scale Systems (Extended Version)
Vitor Enes, Carlos Baquero, Tuanir França Rezende +3
Online applications now routinely replicate their data at multiple sites around the world. In this paper we present Atlas, the first state-machine replication protocol tailored for…