| dc.description.abstract | Digital Twin (DT) technology is an advanced simulation technique that creates virtual replicas of physical entities, enabling real-time simulation and analysis of their operational states within a virtual environment. This technology enhances system visualization and monitoring capabilities and is applied across diverse industries including manufacturing, healthcare, urban planning, and network technology, where it drives significant innovations and changes.
In this thesis, we explore the application of DT technology in monitoring anomaly traffic within network topologies. We employ two virtual machines (VMs): VM1, which represents the physical network, and VM2, which acts as the virtual environment. Both VMs are equipped with Mininet and execute identical topology scripts to ensure consistent network topology across both environments. On VM1, the Scapy tool is used to capture and filter the source and destination addresses of Internet Control Message Protocol (ICMP) traffic. This data is converted into JavaScript Object Notation (JSON) format and transmitted to VM2 using Socket technology. VM2 then replays this traffic on its virtual topology to simulate the behavior of the physical network.
Through this setup, we replicate physical network operations in a virtual environment to compare normal and abnormal traffic behaviors. This enhances our understanding of network anomalies and validates digital twin technology for network security monitoring. Our findings show that digital twins can simulate and analyze network anomalies in real-time without disrupting physical operations. This is crucial for designing secure and stable networks, allowing administrators to anticipate and respond to anomalies, improve resilience, reduce downtime, and optimize performance. | en_US |