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A cloud-driven support layer for enhancing distributed IDS in IoT networks

2026Artigo científico Acesso aberto
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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorFunchal, Gustavo Silva
dc.contributor.authorPedrosa, Tiago
dc.contributor.authorPrieta, Fernando De la
dc.contributor.authorLeitão, Paulo
dc.date.accessioned2026-02-24T10:48:45Z
dc.date.available2026-02-24T10:48:45Z
dc.date.issued2026
dc.description.abstractThe exponential growth of connected devices, including sensors, mobile equipment, and various Internet of Things (IoT) nodes, has significantly increased the volume of data generated at the edge. Traditionally, data analysis tasks are offloaded to centralized cloud servers, resulting in increased latency, bandwidth bottlenecks and privacy concerns. While edge computing addresses these limitations by enabling local processing, it also faces challenges related to limited computational capacity and isolated decision-making. In this context, Multi-Agent Systems provide a promising solution by enabling collaboration among edge nodes for distributed machine learning-based intrusion detection. This work extends previous research by introducing a hierarchical approach within the edge-cloud continuum, where agents deployed in the cloud continuously monitor edge-level behaviour and employ reinforcement learning techniques to suggest dynamic updates to decision parameters of edge agents. This feedback-driven mechanism allows agents to adapt their behaviour over time, improving detection accuracy and collaboration efficiency while keeping communication overhead under control. The proposed architecture balances decentralisation and adaptability, offering a scalable and privacy-preserving solution for intrusion detection in dynamic and resource-constrained IoT environments.eng
dc.description.sponsorshipOpen access funding provided by FCT|FCCN (b-on). This work has been supported by national funds through FCT/MCTES (PIDDAC): CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499/UIDP/05757/2020); and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020). This work has been also supported and received funding from “CyberPRAISE - Cybersecurity research for PRivAte, Intelligent and truStablE solutions” - NORTE2030-FEDER-01820300. The author Gustavo Funchal thanks the FCT Portugal for the PhD Grant 2022.13712.BD.
dc.identifier.citationFunchal, Gustavo; Pedrosa, Tiago; Prieta, De La Fernando; Leitão, Paulo (2026). A cloud-driven support layer for enhancing distributed IDS in IoT networks. SN Computer Science. DOI: 10.1007/2661-8907. 7:2, p. 1-19
dc.identifier.doi10.1007/s42979-026-04750-x
dc.identifier.issn2661-8907
dc.identifier.urihttp://hdl.handle.net/10198/35834
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Science and Business Media LLC
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relation.ispartofSN Computer Science
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectCloud computing
dc.subjectComputational intelligence
dc.subjectIntelligence infrastructure
dc.subjectInternet of things
dc.subjectSmart infrastructure
dc.subjectArtificial intelligence
dc.subjectInternet of things applications in smart
dc.subjectEnvironments
dc.titleA cloud-driven support layer for enhancing distributed IDS in IoT networkseng
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.endPage19
oaire.citation.issue2
oaire.citation.startPage1
oaire.citation.titleSN Computer Science
oaire.citation.volume7
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFunchal
person.familyNamePedrosa
person.familyNameLeitão
person.givenNameGustavo Silva
person.givenNameTiago
person.givenNamePaulo
person.identifierhttps://scholar.google.com/citations?user=eegfgI4AAAAJ&hl=pt-PT&oi=ao
person.identifierA-8390-2011
person.identifier.ciencia-id9416-F3F1-B3EF
person.identifier.ciencia-idB81E-0583-AEDF
person.identifier.ciencia-id8316-8F13-DA71
person.identifier.orcid0000-0002-9691-9956
person.identifier.orcid0000-0003-4873-2705
person.identifier.orcid0000-0002-2151-7944
person.identifier.ridG-2249-2011
person.identifier.scopus-author-id57216637887
person.identifier.scopus-author-id35318153700
person.identifier.scopus-author-id35584388900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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