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dc.contributor.authorUstun, Taha Selim
dc.contributor.authorHussain, S. M. Suhail
dc.contributor.authorUlutas, Ahsen
dc.contributor.authorOnen, Ahmet
dc.contributor.authorRoomi, Muhammad M.
dc.contributor.authorMashima, Daisuke
dc.date.accessioned2022-03-04T06:37:52Z
dc.date.available2022-03-04T06:37:52Z
dc.date.issued2021en_US
dc.identifier.issn2073-8994
dc.identifier.urihttps //doi.org/10.3390/sym13050826
dc.identifier.urihttps://hdl.handle.net/20.500.12573/1226
dc.descriptionThis work was supported by the Ministry of Energy, Transportation and Industry, METI, Japan.en_US
dc.description.abstractIncreased connectivity is required to implement novel coordination and control schemes. IEC 61850-based communication solutions have become popular due to many reasons-object-oriented modeling capability, interoperable connectivity and strong communication protocols, to name a few. However, communication infrastructure is not well-equipped with cybersecurity mechanisms for secure operation. Unlike online banking systems that have been running such security systems for decades, smart grid cybersecurity is an emerging field. To achieve security at all levels, operational technology-based security is also needed. To address this need, this paper develops an intrusion detection system for smart grids utilizing IEC 61850's Generic Object-Oriented Substation Event (GOOSE) messages. The system is developed with machine learning and is able to monitor the communication traffic of a given power system and distinguish normal events from abnormal ones, i.e., attacks. The designed system is implemented and tested with a realistic IEC 61850 GOOSE message dataset under symmetric and asymmetric fault conditions in the power system. The results show that the proposed system can successfully distinguish normal power system events from cyberattacks with high accuracy. This ensures that smart grids have intrusion detection in addition to cybersecurity features attached to exchanged messages.en_US
dc.description.sponsorshipMinistry of Energy, Transportation and Industry, METI, Japanen_US
dc.language.isoengen_US
dc.publisherMDPIST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLANDen_US
dc.relation.isversionof10.3390/sym13050826en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectsmart grid cybersecurityen_US
dc.subjectGOOSE message securityen_US
dc.subjectIEC 62351en_US
dc.subjectintrusion detectionen_US
dc.subjectartificial intelligenceen_US
dc.titleMachine Learning-Based Intrusion Detection for Achieving Cybersecurity in Smart Grids Using IEC 61850 GOOSE Messagesen_US
dc.typearticleen_US
dc.contributor.departmentAGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümüen_US
dc.contributor.institutionauthorOnen, Ahmet
dc.identifier.volumeVolume 13 Issue 5en_US
dc.relation.journalSYMMETRY-BASELen_US
dc.relation.publicationcategoryMakale - Uluslararası - Editör Denetimli Dergien_US


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