Security for a multi-agent cyber-physical conveyor system using machine learning

Funchal, Gustavo Silva; Pedrosa, Tiago; Vallim, Marcos; Leitão, Paulo

Publication

Security for a multi-agent cyber-physical conveyor system using machine learning

2020Conference paper

dc.contributor.author	Funchal, Gustavo Silva
dc.contributor.author	Pedrosa, Tiago
dc.contributor.author	Vallim, Marcos
dc.contributor.author	Leitão, Paulo
dc.date.accessioned	2023-03-03T14:47:24Z
dc.date.available	2023-03-03T14:47:24Z
dc.date.issued	2020
dc.description.abstract	One main foundation of Industry 4.0 is the connectivity of devices and systems using Internet of Things (IoT) technologies, where Cyber-physical systems (CPS) act as the backbone infrastructure based on distributed and decentralized structures. This approach provides significant benefits, namely improved performance, responsiveness and reconfigurability, but also brings some problems in terms of security, as the devices and systems become vulnerable to cyberattacks. This paper describes the implementation of several mechanisms to increase the security in a self-organized cyber-physical conveyor system, based on multi-agent systems (MAS) and build up with different individual modular and intelligent conveyor modules. For this purpose, the JADE-S add-on is used to enforce more security controls, also an Intrusion Detection System (IDS) is created supported by Machine Learning (ML) techniques that analyses the communication between agents, enabling to monitor and analyse the events that occur in the system, extracting signs of intrusions, together they contribute to mitigate cyberattacks.	pt_PT
dc.description.version	info:eu-repo/semantics/publishedVersion	pt_PT
dc.identifier.citation	Funchal, Gustavo; Pedrosa, Tiago; Vallim, Marcos; Leitão, Paulo (2020). Security for a multi-agent cyber-physical conveyor system using machine learning. In 2020 IEEE 18th International Conference on Industrial Informatics (INDIN). Warwick, United Kingdom. p. 47-52	pt_PT
dc.identifier.doi	10.1109/INDIN45582.2020.9478915	pt_PT
dc.identifier.uri	http://hdl.handle.net/10198/27451
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	IEEE	pt_PT
dc.relation.publisherversion	https://ieeexplore.ieee.org/document/9478915	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	pt_PT
dc.subject	Multi-agent systems	pt_PT
dc.subject	Cyber-physical systems	pt_PT
dc.subject	Cybersecurity	pt_PT
dc.subject	Machine learning	pt_PT
dc.subject	Intrusion detection systems	pt_PT
dc.title	Security for a multi-agent cyber-physical conveyor system using machine learning	pt_PT
dc.type	conference paper
dspace.entity.type	Publication
oaire.citation.conferencePlace	Warwick, United Kingdom	pt_PT
oaire.citation.endPage	52	pt_PT
oaire.citation.startPage	47	pt_PT
oaire.citation.title	2020 IEEE 18th International Conference on Industrial Informatics (INDIN)	pt_PT
person.familyName	Funchal
person.familyName	Pedrosa
person.familyName	Leitão
person.givenName	Gustavo Silva
person.givenName	Tiago
person.givenName	Paulo
person.identifier	https://scholar.google.com/citations?user=eegfgI4AAAAJ&hl=pt-PT&oi=ao
person.identifier	A-8390-2011
person.identifier.ciencia-id	9416-F3F1-B3EF
person.identifier.ciencia-id	B81E-0583-AEDF
person.identifier.ciencia-id	8316-8F13-DA71
person.identifier.orcid	0000-0002-9691-9956
person.identifier.orcid	0000-0003-4873-2705
person.identifier.orcid	0000-0002-2151-7944
person.identifier.rid	G-2249-2011
person.identifier.scopus-author-id	57216637887
person.identifier.scopus-author-id	35318153700
person.identifier.scopus-author-id	35584388900
rcaap.rights	openAccess	pt_PT
rcaap.type	conferenceObject	pt_PT
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