Intrusion Detection in Critical Infrastructures: A literature review
dc.cclicence | CC-BY | en |
dc.contributor.author | Fountas, Panagiotis | |
dc.contributor.author | Kouskouras, Taxiarchis | |
dc.contributor.author | Kranas, Georgios | |
dc.contributor.author | Maglaras, Leandros | |
dc.contributor.author | Ferrag, Mohamed Amine | |
dc.date.acceptance | 2021-08-25 | |
dc.date.accessioned | 2021-09-01T09:57:15Z | |
dc.date.available | 2021-09-01T09:57:15Z | |
dc.date.issued | 2021-08-28 | |
dc.description | open access article | en |
dc.description.abstract | ver 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.funder | No external funder | en |
dc.identifier.citation | Fountas, P. et al. (2021) Intrusion Detection in Critical Infrastructures: A literature review. Smart Cities, 4 (3), pp. 1146-1157 | en |
dc.identifier.doi | https://doi.org/10.3390/smartcities4030061 | |
dc.identifier.uri | https://dora.dmu.ac.uk/handle/2086/21214 | |
dc.peerreviewed | Yes | en |
dc.publisher | MDPI | en |
dc.researchinstitute | Cyber Technology Institute (CTI) | en |
dc.subject | cybersecurity | en |
dc.title | Intrusion Detection in Critical Infrastructures: A literature review | en |
dc.type | Article | en |
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