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Edge Multi-agent Intrusion Detection System Architecture for IoT Devices with Cloud Continuum

2024Conference paper Open access
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dc.contributor.authorFunchal, Gustavo Silva
dc.contributor.authorPedrosa, Tiago
dc.contributor.authorPrieta Pintado, Fernando De la
dc.contributor.authorLeitão, Paulo
dc.date.accessioned2024-07-23T14:57:58Z
dc.date.available2024-07-23T14:57:58Z
dc.date.issued2024
dc.description.abstractThe Industry 4.0 has brought significant changes in production processes and business models worldwide. Advanced technologies, e.g., Collaborative Robotics, Artificial Intelligence, Cloud Computing, and Internet of Things (IoT) are playing a crucial role in improving efficiency and productivity. However, the adoption of these technologies, particularly IoT, introduces security vulnerabilities and potential attacks due to inadequate security measures. This paper addresses the need for dedicated cybersecurity mechanisms and secure device design in IoT networks, particularly emphasizing the challenges faced in implementing Intrusion Detection Systems (IDS) on resourceconstrained IoT edge devices, limiting the use of traditional machine learning based detection methods. Moreover, the limited computational resources of IoT devices require lightweight techniques that have low power requirements but can accurately detect anomalies in the network. To tackle these challenges, a novel multi-agent based architecture is proposed, considering the distribution of nodes along the edge-cloud continuum, and enabling the collaboration among different processes to detect anomalies during attacks. The proposed architecture is evaluated at the edge level using the CICIoT2023 dataset. The results demonstrate the feasibility of using multi-agent systems for a collaborative detection of IoT attacks, contributing to enhance the security of IoT-based systems against cyber threats in Industry 4.0 environments by leveraging lightweight techniques.pt_PT
dc.description.sponsorshipThis work has been supported by the Foundation for Science and Technology (FCT, Portugal) through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). The author Gustavo Funchal thanks the FCT for the PhD Grant 2022.13712.BD.
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFunchal, Gustavo; Pedrosa, Tiago; Prieta, Fernando de la; Leitao, Paulo (2024). Edge Multi-agent Intrusion Detection System Architecture for IoT Devices with Cloud Continuum. In 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS). IEEE, p. 1-6. ISBN 979-8-3503-6301-2pt_PT
dc.identifier.doi10.4018/979-8-3693-2137-9.ch003pt_PT
dc.identifier.isbn979-8-3503-6301-2
dc.identifier.urihttp://hdl.handle.net/10198/30069
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relationDeployment of AI-based algorithms along the edge-to-cloud to enhance the cybersecurity in IoT applications
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/pt_PT
dc.subjectIntrusion Detection Systemspt_PT
dc.subjectMulti-agent Systemspt_PT
dc.subjectInternet of Things
dc.subjectMachine Learning
dc.titleEdge Multi-agent Intrusion Detection System Architecture for IoT Devices with Cloud Continuumpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardTitleDeployment of AI-based algorithms along the edge-to-cloud to enhance the cybersecurity in IoT applications
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//2022.13712.BD/PT
oaire.citation.endPage6pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
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.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
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
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