Title
Leveraging Digital Twins and SIEM Integration for Incident Response in OT EnvironmentsAuthor
xmlui.dri2xhtml.METS-1.0.item-contributorOtherinstitution
https://ror.org/03hp1m080Version
http://purl.org/coar/version/c_970fb48d4fbd8a85
Rights
© 2024 The AuthorsAccess
http://purl.org/coar/access_right/c_abf2xmlui.dri2xhtml.METS-1.0.item-identifier
https://hdl.handle.net/11441/160432Published at
IX Jornadas Nacionales de Investigación en Ciberseguridad (JNIC) Pp. 294-301. Sevilla, 27-29 de Mayo, 2024Publisher
Universidad de SevillaKeywords
IIoT
digital twins
threat detection
incident response ... [+]
digital twins
threat detection
incident response ... [+]
IIoT
digital twins
threat detection
incident response
attack detection [-]
digital twins
threat detection
incident response
attack detection [-]
Abstract
The Industrial Internet of Things (IIoT) has digitally transformed industrial processes albeit at the expense of increasing exposure to new security threats. System Information and Event Management (S ... [+]
The Industrial Internet of Things (IIoT) has digitally transformed industrial processes albeit at the expense of increasing exposure to new security threats. System Information and Event Management (SIEM) systems, typically designed for Information Technology (IT), may struggle with the high data volume, specialized security needs, and real-time response requirements of IIoT environments. Digital Twins (DT), virtual replicas of physical devices, offer a solution to these challenges. By integrating SIEM with DT, incident response can be automated in Operational Technology (OT) environments. This integration enhances real-time threat detection, response coordination and post-incident tasks to ensure the security and continuity of industrial operations. A use case and prototype validate the effectiveness of this approach and highlight its potential to strengthen OT security in the face of evolving threats. [-]
xmlui.dri2xhtml.METS-1.0.item-oaire-funderName
Comisión EuropeaGobierno Vasco
xmlui.dri2xhtml.METS-1.0.item-oaire-fundingStream
H2020Elkartek 2023
xmlui.dri2xhtml.METS-1.0.item-oaire-awardNumber
101021911KK-2023-00085
xmlui.dri2xhtml.METS-1.0.item-oaire-awardURI
https://doi.org/10.3030/101021911Sin información
xmlui.dri2xhtml.METS-1.0.item-oaire-awardTitle
A Cognitive Detection System for Cybersecure Operational Technologies (IDUNN)cyBErsecure industriAl Computing cONtinuum (BEACON)
Collections
The following license files are associated with this item: