Intrusion Detection of Local Area Network Using Digital Twin Technology

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dc.contributor.authorAmusan, A.A
dc.contributor.authorAmusan, E.A
dc.contributor.authorAdeniyi, E.O
dc.date.accessioned2025-08-24T16:09:20Z
dc.date.available2025-08-24T16:09:20Z
dc.date.issued2024
dc.descriptionScholarly article
dc.description.abstractThe rapid growth of Local Area Networks (LANs) in critical infrastructure necessitates robust security measures to mitigate threats such as intrusions. This paper presents a novel approach to LAN intrusion detection using digital twin technology integrated with a variety of tools, including the Fiware Orion Context Broker, Grafana IoT Agent, Firebase, and Flutter. The digital twin replicates the physical LAN environment in real-time, facilitating enhanced monitoring and real-time threat detection. The system uses Snort 3 as a network intrusion detection system (NIDS) to monitor network traffic and sends alerts through a pipeline that involves the Fiware IoT Agent and Orion Context Broker, creating a real-time digital twin model of the LAN infrastructure. The visualizations of network conditions and intrusion status are provided through Grafana, while the mobile user interface is developed using Flutter, with Firebase providing backend data synchronization and notifications. Experimental results demonstrate the effectiveness of the system in detecting and reporting various types of network intrusions, offering enhanced network security through comprehensive monitoring and real-time alerting. This study contributes to the evolving field of LAN security by showcasing a practical implementation of digital twin technology in intrusion detection.
dc.identifier.citationAmusan, A. A., Adeniyi, E. O., & Amusan, E. A. (2024). Intrusion detection of local area network using digital twin technology. University of Pitesti Scientific Bulletin, Series: Electronics and Computer Science, 24(2), 21–32. Editura Universitatii din Pitesti.
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/13371
dc.language.isoen
dc.publisherEditura Universitatii din Pitesti
dc.titleIntrusion Detection of Local Area Network Using Digital Twin Technology
dc.typeArticle
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