RT Conference Proceedings
T1 Deployment of Secure Machine Learning Pipelines for Near-Real-Time Control of 6G Network Services
A1 González, Pol
A1 Zahir, Adam
A1 Grasselli, Chiara
A1 Muñiz, Alejandro
A1 Ggroshev, Milan
A1 Barzegar, Sima
A1 Callegati, Franco
A1 Careglio, Davide
A1 Ruiz, Marc
A1 Velasco, Luis
AB A ML function orchestrator deploying secure ML pipelines to support near-real-time control of network services is demonstrated. A distributed ledger supports the initial key exchange to establish secure connectivity among the agents in the pipeline
YR 2023
FD 2023
LK https://hdl.handle.net/10016/39151
UL https://hdl.handle.net/10016/39151
LA eng
NO This paper has been submitted at : Optical Fiber Communication Conference 2024
NO The research leading to these results has received funding from the Smart Networks and Services Joint Undertaking under the European Union's Horizon Europe researchand innovation programme under G.A. No. 101096466 (DESIRE6G) from the MICINN IBON (PID2020-114135RB-I00) projects and from the ICREA Institution
DS e-Archivo
RD 17 jul. 2024