contINuous deCentralized lEarNing of ioT devIces' behaVioural profilEs

Informazioni relative al progetto

INCENTIVE

ID dell’accordo di sovvenzione: 101065524

DOI

10.3030/101065524

Progetto chiuso

Data della firma CE 14 Luglio 2022

Data di avvio 1 Marzo 2023

Data di completamento 30 Aprile 2025

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 181 152,96

Coordinato da

UNIVERSIDAD DE MURCIA
Spain

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected, processed or generated by the action. It is a document describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved.

Documents, reports (1)

Communication, Dissemination & Outreach Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Pubblicazioni

Peer reviewed articles (4)

Federated learning for misbehaviour detection with variational autoencoders and Gaussian mixture models

Autori: Enrique Mármol Campos, Aurora Gonzalez-Vidal, José L. Hernández-Ramos, Antonio Skarmeta
Pubblicato in: International Journal of Information Security, Numero 24, 2025, ISSN 1615-5262
Editore: Springer Science and Business Media LLC
DOI: 10.1007/s10207-025-01000-8

Misbehavior detection in intelligent transportation systems based on federated learning

Autori: Enrique Mármol Campos, José L. Hernandez-Ramos, Aurora González Vidal, Gianmarco Baldini, Antonio Skarmeta
Pubblicato in: Internet of Things, Numero 25, 2024, ISSN 2542-6605
Editore: Elsevier BV
DOI: 10.1016/j.iot.2024.101127

Intrusion Detection Based on Federated Learning: A Systematic Review

Autori: Jose Hernandez-Ramos, Georgios Karopoulos, Efstratios Chatzoglou, Vasileios Kouliaridis, Enrique Marmol, Aurora Gonzalez-Vidal, Georgios Kambourakis
Pubblicato in: ACM Computing Surveys, 2025, ISSN 0360-0300
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3731596

FedRDF: A Robust and Dynamic Aggregation Function Against Poisoning Attacks in Federated Learning

Autori: Enrique Mármol Campos, Aurora Gonzalez-Vidal, José L. Hernández-Ramos, Antonio Skarmeta
Pubblicato in: IEEE Transactions on Emerging Topics in Computing, Numero 13, 2025, ISSN 2168-6750
Editore: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/TETC.2024.3474484