Enhancing Intrusion Detection Systems with Digital Twin Technology for Cyber-Physical Security

The need for strong security measures to ward off complex cyber-attacks has grown in tandem with the exponential growth of cyber-physical systems (CPS) and Internet of Things (IoT) devices. This paper lays forth a thorough plan to improve cyber-physical security by bolstering intrusion detection systems (IDS) with the use of digital twin technology (DTT). Virtual representations of physical systems, or "digital twins," allow for sophisticated modelling, predictive analytics, and real-time monitoring. Incorporating DTT with IDS allows for proactive and dynamic threat detection and response in this system. Datasets generated by an ICS testbed— a device designed to monitor storage reservoir water levels and turbulence—form the basis of the suggested architecture. The SCADA system uses a number of indicators to assess the efficacy of several machine learning (ML) models that are used to detect and categorize intrusions. The findings show that ML approaches are great at detecting intrusions, with low false positive rates and high detection rates. Also, the IDS can now identify more complex and unique assaults because to DTT's incorporation, which enables continuous system learning and adaptability. An important step forward in cyber-physical security, this research shows that digital twins have the ability to change intrusion detection systems (IDS) from reactive to proactive. The framework offers a durable and scalable approach to safeguard vital infrastructures from ever-changing cyber threats, and its ramifications reach into a wide range of industrial applications. The integration of Digital Twin Technology (DTT) with Intrusion Detection Systems (IDS) for cyber-physical security showed significant improvements in threat detection. Test results revealed a 40% increase in early intrusion detection accuracy compared to traditional IDS models. Additionally, proactive system adaptations through DTT reduced response time to potential threats by 25%, enhancing overall system resilience