Publication: Deployment of Secure Machine Learning Pipelines for Near-Real-Time Control of 6G Network Services
dc.affiliation.dpto | UC3M. Departamento de Ingeniería Telemática | es |
dc.affiliation.grupoinv | UC3M. Grupo de Investigación: Network Technologies | es |
dc.contributor.author | González, Pol | |
dc.contributor.author | Zahir, Adam | |
dc.contributor.author | Grasselli, Chiara | |
dc.contributor.author | Muñiz, Alejandro | |
dc.contributor.author | Ggroshev, Milan | |
dc.contributor.author | Barzegar, Sima | |
dc.contributor.author | Callegati, Franco | |
dc.contributor.author | Careglio, Davide | |
dc.contributor.author | Ruiz, Marc | |
dc.contributor.author | Velasco, Luis | |
dc.contributor.funder | European Commission | en |
dc.date.accessioned | 2023-12-22T09:45:52Z | |
dc.date.available | 2023-12-22T09:45:52Z | |
dc.date.issued | 2023 | |
dc.description | This paper has been submitted at : Optical Fiber Communication Conference 2024 | en |
dc.description.abstract | 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 | en |
dc.description.sponsorship | The research leading to these results has received funding from the Smart Networks and Services Joint Undertaking under the European Union's Horizon Europe research and innovation programme under G.A. No. 101096466 (DESIRE6G) from the MICINN IBON (PID2020-114135RB-I00) projects and from the ICREA Institution | en |
dc.format.extent | 3 | es |
dc.identifier.publicationfirstpage | 1 | es |
dc.identifier.publicationlastpage | 3 | es |
dc.identifier.uri | https://hdl.handle.net/10016/39151 | |
dc.language.iso | eng | es |
dc.relation.eventdate | 24-28 March 2024 | en |
dc.relation.eventplace | San Diego, California, USA | en |
dc.relation.eventtitle | OFC 2024: Optical Fiber Communications Conference | en |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/101096466/DESIRE6G | es |
dc.rights | © 2024 The Authors | en |
dc.rights.accessRights | open access | en |
dc.subject.eciencia | Telecomunicaciones | es |
dc.title | Deployment of Secure Machine Learning Pipelines for Near-Real-Time Control of 6G Network Services | en |
dc.type | conference paper | en |
dc.type.hasVersion | SMUR | en |
dspace.entity.type | Publication |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- deployment_OFC_2024.pdf
- Size:
- 518.15 KB
- Format:
- Adobe Portable Document Format
- Description: