# Building Cyber-Resilient Smart Grids with Digital Twins and Data Spaces
## 2 Digital Twins and Data Spaces
### Data Spaces
Furthermore, the system architecture supports the implementation of IDMEF (Intrusion Detection Message Exchange Format) version 2 [18], allowing for standardized incident reporting and facilitating interoperability between our monitoring systems and external cybersecurity frameworks. The report generated below exemplifies this functionality, detailing an anomalous voltage oscillation at substation T343. Such reports are vital for the prompt diagnosis and rectification of issues, thereby ensuring the reliability and safety of the power distribution network. Moreover, our reporting structure is fully compliant with the IDMEF version 2 standards, which facilitates interoperability and standardized communication within cybersecurity management processes. An example of such an event is given in the following Listing 1. The strategic incorporation of OpenSearch into our framework significantly enhances the operational visibility of the smart grid. It also strengthens the reactive capabilities of our security measures. By providing a comprehensive view of the grid's health and enabling quick detection and communication of potential threats, our approach solidifies the grid's defence against sophisticated cyber attacks, thereby ensuring its continuous and secure operation. Figure 5: Real-time dashboard display of electrical substation parameters. \"Version\": \"2.0.3\", \"ID\": \"a1b2c3d4-5678-90 ab-cdef-1234567890 ab\", \"Entity\": \"Substation T343\", \"Category\": [

\"System.Anomaly.VoltageOscillation\" ], \"Cause\": \"Technical Fault\", \"Description\": \"Anomalous voltage oscillation\", \"Status\": \"Incident\", \"Severity\": \"High\", \"CreateTime\": \"2023-11-05T12:34:56Z\", \"DetectTime\": \"2023-11-05T12:34:55Z\", \"Confidence\": 0.95, \"Analyzer\": {

\"IP\": \"192.168.1.10\", \"Name\": \"Voltage Monitoring System\", \"Hostname\": \"volt-mon.example.com\", \"Type\": \"System\", \"Category\": [

\"SCADA\"

\"Data\": [

\"Voltage Readings\"

], \"Method\": [

\"Automated Monitoring\"

], \"Target\": [

\"Location\": \"Power Grid\"

], \"Vector\": [

\"Category\": \"System\", \"Name\": \"Substation T343\", \"Size\": \"Large\", \"Observable\": [

\"Voltage Oscillation\"

] ], \"Observables\": [

\"Name\": \"Voltage Oscillation\", \"Reference\": \"IDMEFv2\", \"Content\": \"{\"type\":\"Voltage\",\"Value\":\"20.150 kV\"}\"

] ]



### Performance Analysis

In the smart grid context, the responsiveness and scalability of the digital twin are critical, especially for applications, such as smart grids, where real-time data processing is paramount. To this end, we have conducted an in-depth performance analysis of the FIWARE Orion Context Broker, which is crucial in managing the real-time state of digital twins in a smart grid environment. This experiment was designed to simulate a scenario where a multitude of IoT devices, akin to sensors and actuators within a smart grid, concurrently send requests to the Context Broker, thereby mimicking the real-world operational load and data throughput. The Orion Context Broker was deployed on a local server, and the experiment was configured to measure the latency of CRUD operations. The CRUD operations are defined as follows:

* Create: Register a new entity with a unique ID and predefined attributes. * Read: Retrieve the entity's details using its unique ID. * Update: Modify the entity's attributes. * Delete: Remove the entity from the Context Broker. These operations are fundamental to the interaction between IoT devices and the Context Broker, reflecting the typical transactional requirements within a smart grid infrastructure. The performance of these operations directly impacts the efficiency and reliability of the digital twin representation and, by extension, the operational integrity of the smart grid itself. To emulate the concurrent operations from multiple IoT devices, we utilized a Python script that employs the 'concurrent.features' module, allowing us to simulate up to 150 clients interacting with the Context Broker simultaneously.