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Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning

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Resumo:One main foundation of the Industry 4.0 is the connectivity of devices and systems using Internet of Things technologies, where Cyber-physical systems (CPS) act as the backbone infrastructure based on distributed and decentralized structures. CPS requires the use of Artificial Intelligence (AI) techniques, such as Multi-Agent Systems (MAS), allowing the incorporation of intelligence into the CPS through autonomous, proactive and cooperative entities. The adoption of this new generation of systems in the industrial environment opens new doors for various attacks that can cause serious damage to industrial production systems. This work presents the development of security mechanisms for systems based on MAS, where these mechanisms are used in an experimental case study that consists of a multiagent cyber-physical conveyor system. For this purpose, simple security mechanisms were employed in the system, such as user authentication, signature and message encryption, as well as other more complex mechanisms, such as machine learning techniques that allows the agents to be more intelligent in relation to the exchange of messages protecting the system against attacks, through the classification of the messages as reliable or not, and also an intrusion detection system was carried out. Based on the obtained results, the efficient protection of the system was reached, mitigating the main attack vectors present in the system architecture.
Autores principais:Funchal, Gustavo Silva
Assunto:Industry 4.0 Multi-agent systems Cyber-physical systems Cybersecurity Machine learning Intrusion detection systems
Ano:2020
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
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author Funchal, Gustavo Silva
author_facet Funchal, Gustavo Silva
author_role author
contributor_name_str_mv Leitão, Paulo
Barbosa, José
Vallim, Marcos
Biblioteca Digital do IPB
country_str PT
creators_json_txt [{\"Person.name\":\"Funchal, Gustavo Silva\",\"Person.identifier.orcid\":\"0000-0002-9691-9956\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Leitão, Paulo
Barbosa, José
Vallim, Marcos
Biblioteca Digital do IPB
datacite.creators.creator.creatorName.fl_str_mv Funchal, Gustavo Silva
datacite.date.Accepted.fl_str_mv 2020-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2020-12-21T10:14:25Z
datacite.date.embargoed.fl_str_mv 2020-12-21T10:14:25Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Industry 4.0
Multi-agent systems
Cyber-physical systems
Cybersecurity
Machine learning
Intrusion detection systems
datacite.titles.title.fl_str_mv Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
dc.contributor.none.fl_str_mv Leitão, Paulo
Barbosa, José
Vallim, Marcos
Biblioteca Digital do IPB
dc.creator.none.fl_str_mv Funchal, Gustavo Silva
dc.date.Accepted.fl_str_mv 2020-01-01T00:00:00Z
dc.date.available.fl_str_mv 2020-12-21T10:14:25Z
dc.date.embargoed.fl_str_mv 2020-12-21T10:14:25Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10198/22980
dc.language.none.fl_str_mv eng
dc.rights.cclincense.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Industry 4.0
Multi-agent systems
Cyber-physical systems
Cybersecurity
Machine learning
Intrusion detection systems
dc.title.fl_str_mv Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_bdcc
description One main foundation of the Industry 4.0 is the connectivity of devices and systems using Internet of Things technologies, where Cyber-physical systems (CPS) act as the backbone infrastructure based on distributed and decentralized structures. CPS requires the use of Artificial Intelligence (AI) techniques, such as Multi-Agent Systems (MAS), allowing the incorporation of intelligence into the CPS through autonomous, proactive and cooperative entities. The adoption of this new generation of systems in the industrial environment opens new doors for various attacks that can cause serious damage to industrial production systems. This work presents the development of security mechanisms for systems based on MAS, where these mechanisms are used in an experimental case study that consists of a multiagent cyber-physical conveyor system. For this purpose, simple security mechanisms were employed in the system, such as user authentication, signature and message encryption, as well as other more complex mechanisms, such as machine learning techniques that allows the agents to be more intelligent in relation to the exchange of messages protecting the system against attacks, through the classification of the messages as reliable or not, and also an intrusion detection system was carried out. Based on the obtained results, the efficient protection of the system was reached, mitigating the main attack vectors present in the system architecture.
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instname_str Instituto Politécnico de Bragança
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oai_identifier_str oai:bibliotecadigital.ipb.pt:10198/22980
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person_str_mv Funchal, Gustavo Silva
Funchal, Gustavo Silva
https://www.ciencia-id.pt/9416-F3F1-B3EF
9416-F3F1-B3EF
http://orcid.org/0000-0002-9691-9956
0000-0002-9691-9956
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spelling engpt_PTOne main foundation of the Industry 4.0 is the connectivity of devices and systems using Internet of Things technologies, where Cyber-physical systems (CPS) act as the backbone infrastructure based on distributed and decentralized structures. CPS requires the use of Artificial Intelligence (AI) techniques, such as Multi-Agent Systems (MAS), allowing the incorporation of intelligence into the CPS through autonomous, proactive and cooperative entities. The adoption of this new generation of systems in the industrial environment opens new doors for various attacks that can cause serious damage to industrial production systems. This work presents the development of security mechanisms for systems based on MAS, where these mechanisms are used in an experimental case study that consists of a multiagent cyber-physical conveyor system. For this purpose, simple security mechanisms were employed in the system, such as user authentication, signature and message encryption, as well as other more complex mechanisms, such as machine learning techniques that allows the agents to be more intelligent in relation to the exchange of messages protecting the system against attacks, through the classification of the messages as reliable or not, and also an intrusion detection system was carried out. Based on the obtained results, the efficient protection of the system was reached, mitigating the main attack vectors present in the system architecture.application/pdfpt_PTDevelopment of security mechanisms for a multi-agent cyber-physical conveyor system using machine learningPersonalFunchal, Gustavo SilvaDSpacehttp://dspace.org/items/4db24fee-2be5-4feb-966f-acb5a7ff1a5cDSpacehttp://dspace.org/items/4db24fee-2be5-4feb-966f-acb5a7ff1a5cFunchalGustavo SilvaCiência IDhttps://www.ciencia-id.pt9416-F3F1-B3EFORCIDhttp://orcid.org0000-0002-9691-9956Scopus Author IDhttps://www.scopus.com57216637887Leitão, PauloBarbosa, JoséVallim, MarcosHostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptURNurn:tid:2025598662020-12-21T10:14:25Z202020192020-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/22980http://purl.org/coar/access_right/c_abf2open accessIndustry 4.0Multi-agent systemsCyber-physical systemsCybersecurityMachine learningIntrusion detection systems3320827 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesis2020http://creativecommons.org/licenses/by-nc/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/5c8e6ad1-56c9-4493-8abb-c2f19e39bf41/download
spellingShingle Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
Funchal, Gustavo Silva
Industry 4.0
Multi-agent systems
Cyber-physical systems
Cybersecurity
Machine learning
Intrusion detection systems
status SINGLETON
subject.fl_str_mv Industry 4.0
Multi-agent systems
Cyber-physical systems
Cybersecurity
Machine learning
Intrusion detection systems
title Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
title_full Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
title_fullStr Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
title_full_unstemmed Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
title_short Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
title_sort Development of security mechanisms for a multi-agent cyber-physical conveyor system using machine learning
topic Industry 4.0
Multi-agent systems
Cyber-physical systems
Cybersecurity
Machine learning
Intrusion detection systems
topic_facet Industry 4.0
Multi-agent systems
Cyber-physical systems
Cybersecurity
Machine learning
Intrusion detection systems
url http://hdl.handle.net/10198/22980
visible 1