Repository logo
 
Publication

Holistic Security and Safety for Factories of the Future

2022Journal article Open access
Simple item page
dc.contributor.authorMaia, Eva
dc.contributor.authorWannous, Sinan
dc.contributor.authorDias, Tiago
dc.contributor.authorPraça, Isabel
dc.contributor.authorFaria, Ana
dc.date.accessioned2023-01-25T11:27:29Z
dc.date.available2023-01-25T11:27:29Z
dc.date.issued2022
dc.description.abstractThe accelerating transition of traditional industrial processes towards fully automated and intelligent manufacturing is being witnessed in almost all segments. This major adoption of enhanced technology and digitization processes has been originally embraced by the Factories of the Future and Industry 4.0 initiatives. The overall aim is to create smarter, more sustainable, and more resilient future-oriented factories. Unsurprisingly, introducing new production paradigms based on technologies such as machine learning (ML), the Internet of Things (IoT), and robotics does not come at no cost as each newly incorporated technique poses various safety and security challenges. Similarly, the integration required between these techniques to establish a unified and fully interconnected environment contributes to additional threats and risks in the Factories of the Future. Accumulating and analyzing seemingly unrelated activities, occurring simultaneously in different parts of the factory, is essential to establish cyber situational awareness of the investigated environment. Our work contributes to these efforts, in essence by envisioning and implementing the SMS-DT, an integrated platform to simulate and monitor industrial conditions in a digital twin-based architecture. SMS-DT is represented in a three-tier architecture comprising the involved data and control flows: edge, platform, and enterprise tiers. The goal of our platform is to capture, analyze, and correlate a wide range of events being tracked by sensors and systems in various domains of the factory. For this aim, multiple components have been developed on the basis of artificial intelligence to simulate dominant aspects in industries, including network analysis, energy optimization, and worker behavior. A data lake was also used to store collected information, and a set of intelligent services was delivered on the basis of innovative analysis and learning approaches. Finally, the platform was tested in a textile industry environment and integrated with its ERP system. Two misuse cases were simulated to track the factory machines, systems, and people and to assess the role of SMS-DT correlation mechanisms in preventing intentional and unintentional actions. The results of these misuse case simulations showed how the SMS-DT platform can intervene in two domains in the first scenario and three in the second one, resulting in correlating the alerts and reporting them to security operators in the multi-domain intelligent correlation dashboard.pt_PT
dc.description.sponsorshipThe present work has been developed under the EUREKA ITEA3 Project Cyber-Factory#1 (ITEA-17032) and Project CyberFactory#1PT (ANI—P2020 40124) co-funded by Portugal 2020. Furthermore, this work also received funding from the project UIDB/00760/2020.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/s22249915pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/21849
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationITEA-17032pt_PT
dc.relationANI—P2020 40124pt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/22/24/9915pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectSmart factoriespt_PT
dc.subjectCybersecuritypt_PT
dc.subjectIndustry 4.0pt_PT
dc.subjectMulti-domain security and safetypt_PT
dc.subjectdigital twinspt_PT
dc.subjectSecurity of Factories of the Futurept_PT
dc.titleHolistic Security and Safety for Factories of the Futurept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT
oaire.citation.issue24pt_PT
oaire.citation.startPage9915pt_PT
oaire.citation.titleSensorspt_PT
oaire.citation.volume22pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMaia
person.familyNameWannous
person.familyNameDias
person.familyNamePraça
person.givenNameEva
person.givenNameSinan
person.givenNameTiago Fontes
person.givenNameIsabel
person.identifierYuJaY1sAAAAJ
person.identifier2140741
person.identifier299522
person.identifier.ciencia-id4F14-EF83-C4B9
person.identifier.ciencia-id6813-6CB1-E8BD
person.identifier.ciencia-idF510-7CAD-42CD
person.identifier.ciencia-idC710-4218-1BFF
person.identifier.orcid0000-0002-8075-531X
person.identifier.orcid0000-0002-9711-4850
person.identifier.orcid0000-0002-1693-7872
person.identifier.orcid0000-0002-2519-9859
person.identifier.ridK-8430-2014
person.identifier.scopus-author-id57355096600
person.identifier.scopus-author-id22734900800
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication47a108c4-cf8a-46f3-8954-90624174e8fc
relation.isAuthorOfPublication1f297ae3-efa6-4ccb-b0f0-7f4d815f1aa3
relation.isAuthorOfPublicationdd54c1b5-5e59-4f2d-8018-15d06880f4bb
relation.isAuthorOfPublicationee4ecacd-c6c6-41e8-bca1-21a60ff05f50
relation.isAuthorOfPublication.latestForDiscoveryee4ecacd-c6c6-41e8-bca1-21a60ff05f50
relation.isProjectOfPublicationdb3e2edb-b8af-487a-b76a-f6790ac2d86e
relation.isProjectOfPublication.latestForDiscoverydb3e2edb-b8af-487a-b76a-f6790ac2d86e

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ART_GECAD_ICP_sensors_2022.pdf
Size:
7.15 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ISEP – GECAD – Artigos