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dc.contributor.authorKaasen, Andreas Dybviken_GB
dc.contributor.authorGrov, Gudmunden_GB
dc.contributor.authorMancini, Federicoen_GB
dc.contributor.authorBaksaas, Magnusen_GB
dc.date.accessioned2023-03-30T06:51:52Z
dc.date.accessioned2023-05-05T13:52:51Z
dc.date.available2023-03-30T06:51:52Z
dc.date.available2023-05-05T13:52:51Z
dc.date.issued2022-11-28
dc.identifier.citationKaasen, Grov G, Mancini F, Baksaas M. Towards data-driven autonomous cyber defence for military unmanned vehicles - threats & attacks. MILCOM IEEE Military Communications Conference. 2023en_GB
dc.identifier.urihttp://hdl.handle.net/20.500.12242/3179
dc.descriptionMILCOM IEEE Military Communications Conference 2023en_GB
dc.description.abstractUnmanned vehicles with varying degrees of autonomy will likely change the way military operations can be conducted, but they also introduce risks that require new ways of thinking security. In particular, the safety ramifications of cyber attacks should be seen as equally critical as the loss of classified data. Developing a cyber defence capability that can detect and manage these potentially harmful events also without human intervention thus becomes a fundamental requirement. In this paper, we commence such work by exploring how to disrupt the functionality of an actual military unmanned ground vehicle given an internal attacker, and how the resulting data can be used to design an an effective detection capability.en_GB
dc.language.isoenen_GB
dc.subjectUbemannede systemeren_GB
dc.subjectUbemannede kjøretøyeren_GB
dc.titleTowards data-driven autonomous cyber defence for military unmanned vehicles - threats & attacksen_GB
dc.typeArticleen_GB
dc.date.updated2023-03-30T06:51:52Z
dc.identifier.cristinID2137413
dc.identifier.doihttps://doi.org/10.1109/BigData55660.2022.10020248
dc.source.issn2155-7578
dc.source.issn2155-7586
dc.type.documentJournal article
dc.relation.journalMILCOM IEEE Military Communications Conference


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