Repository logo
 
Publication

Attack Detection in Cyber-Physical Production Systems using the Deterministic Dendritic Cell Algorithm

2020Conference object Restricted access
Simple item page
dc.contributor.authorPinto, Rui
dc.contributor.authorGonçalves, Gil
dc.contributor.authorTovar, Eduardo
dc.contributor.authorDelsing, Jerker
dc.date.accessioned2020-10-30T09:56:46Z
dc.date.embargo2120
dc.date.issued2020
dc.description.abstractCyber-Physical Production Systems (CPPS) are key enablers for industrial and economic growth. The introduction of the Internet of Things (IoT) in industrial processes represents a new revolution towards the Smart Manufacturing oncept and is usually designated as the 4 th Industrial Revolution. Despite the huge interest from the industry to innovate their production systems, in order to increase revenues at lower costs, the IoT concept is still immature and fuzzy, which increases security related risks in industrial systems. Facing this paradigm and, since CPPS have reached a level of complexity, where the human intervention for operation and control is becoming increasingly difficult, Smart Factories require autonomic methodologies for security management and self-healing. This paper presents an Intrusion Detection System (IDS) approach for CPPS, based on the deterministic Dendritic Cell Algorithm (dDCA). To evaluate the dDCA effectiveness, a testing dataset was generated, by implementing and injecting various attacks on a OPC UA based CPPS testbed. The results show that these attacks can be successfully detected using the dDCA.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/ETFA46521.2020.9212021pt_PT
dc.identifier.issn1946-0759
dc.identifier.urihttp://hdl.handle.net/10400.22/16376
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9212021pt_PT
dc.subjectCPPSpt_PT
dc.subjectOPC UApt_PT
dc.subjectIDSpt_PT
dc.subjectDCApt_PT
dc.subjectAISpt_PT
dc.subjectNetwork Attackspt_PT
dc.titleAttack Detection in Cyber-Physical Production Systems using the Deterministic Dendritic Cell Algorithmpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceVienna, Austriapt_PT
oaire.citation.endPage1559pt_PT
oaire.citation.startPage1552pt_PT
oaire.citation.titleProceedings of the 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2020)pt_PT
person.familyNameTovar
person.givenNameEduardo
person.identifier.ciencia-id6017-8881-11E8
person.identifier.orcid0000-0001-8979-3876
person.identifier.scopus-author-id7006312557
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication80b63d8a-2e6d-484e-af3c-55849d0cb65e
relation.isAuthorOfPublication.latestForDiscovery80b63d8a-2e6d-484e-af3c-55849d0cb65e

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
COM_CISTER_Pinto_2020.pdf
Size:
655.65 KB
Format:
Adobe Portable Document Format
Download

Collections

ISEP – CISTER – Comunicações em eventos científicos