Intrusion Detection in Critical Infrastructures: A literature review

dc.cclicenceCC-BYen
dc.contributor.authorFountas, Panagiotis
dc.contributor.authorKouskouras, Taxiarchis
dc.contributor.authorKranas, Georgios
dc.contributor.authorMaglaras, Leandros
dc.contributor.authorFerrag, Mohamed Amine
dc.date.acceptance2021-08-25
dc.date.accessioned2021-09-01T09:57:15Z
dc.date.available2021-09-01T09:57:15Z
dc.date.issued2021-08-28
dc.descriptionopen access articleen
dc.description.abstractver the years, the digitization of all aspects of life in modern societies is considered an acquired advantage. However, like the terrestrial world, the digital world is not perfect and many dangers and threats are present. In the present work, we conduct a systematic review of the methods of network detection and cyber attacks that can take place in critical infrastructure. As it is shown, the implementation of a system that learns from the system behavior (machine learning), on multiple levels and spots any diversity, is one of the most effective solutions.en
dc.funderNo external funderen
dc.identifier.citationFountas, P. et al. (2021) Intrusion Detection in Critical Infrastructures: A literature review. Smart Cities, 4 (3), pp. 1146-1157en
dc.identifier.doihttps://doi.org/10.3390/smartcities4030061
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/21214
dc.peerreviewedYesen
dc.publisherMDPIen
dc.researchinstituteCyber Technology Institute (CTI)en
dc.subjectcybersecurityen
dc.titleIntrusion Detection in Critical Infrastructures: A literature reviewen
dc.typeArticleen

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