most citedDecentralised and collaborative machine learning framework for IoT

17 citations · 35 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR2024

Attribute-Based Authentication in Secure Group Messaging for Distributed Environments and Safer Online Spaces

David Soler, Carlos Dafonte, Manuel Fernández-Veiga +2

The Messaging Layer security (MLS) and its underlying Continuous Group Key Agreement (CGKA) protocol allows a group of users to share a cryptographic secret in a dynamic manner, su…

cs.LG2024★ 1 cited

Privacy-aware Berrut Approximated Coded Computing for Federated Learning

Xavier Martínez Luaña, Rebeca P. Díaz Redondo, Manuel Fernández Veiga

Federated Learning (FL) is an interesting strategy that enables the collaborative training of an AI model among different data owners without revealing their private datasets. Even…

cs.NI2024★ 10 cited

QKDNetSim+: Improvement of the Quantum Network Simulator for NS-3

David Soler, Iván Cillero, Carlos Dafonte +3

The first Quantum Key Distribution (QKD) networks are currently being deployed, but the implementation cost is still prohibitive for most researchers. As such, there is a need for…

cs.CR2024★ 7 cited

A Privacy-preserving key transmission protocol to distribute QRNG keys using zk-SNARKs

David Soler, Carlos Dafonte, Manuel Fernández-Veiga +2

High-entropy random numbers are an essential part of cryptography, and Quantum Random Number Generators (QRNG) are an emergent technology that can provide high-quality keys for cry…

cs.LG2023★ 17 cited

Decentralised and collaborative machine learning framework for IoT

Martín González-Soto, Rebeca P. Díaz-Redondo, Manuel Fernández-Veiga +2

Decentralised machine learning has recently been proposed as a potential solution to the security issues of the canonical federated learning approach. In this paper, we propose a d…

cs.LG2023

A Blockchain Solution for Collaborative Machine Learning over IoT

Carlos Beis-Penedo, Francisco Troncoso-Pastoriza, Rebeca P. Díaz-Redondo +3

The rapid growth of Internet of Things (IoT) devices and applications has led to an increased demand for advanced analytics and machine learning techniques capable of handling the…