# Building Cyber-Resilient Smart Grids with Digital Twins and Data Spaces
## 2 Digital Twins and Data Spaces
### Data Spaces
Regarding data stewardship, FIWARE incorporates MongoDB, which lays the groundwork for preserving the system's real-time data integrity. The segregation of real-time and historical data is a strategic approach that enhances the performance and efficiency of data management systems, especially in the context of a digital twin. Real-time data are dynamic and constantly changing, and they require immediate processing to accurately reflect the current state of the physical infrastructure. These data are typically transient and are stored in high-performance databases like MongoDB, which the FIWARE Orion Context Broker uses. Such databases are optimized for speed and low-latency access, ensuring that the digital twin is a real-time representation of the physical counterpart. Historical data, on the other hand, consist of time-series records of past states and events. These data are invaluable for trend analysis, predictive maintenance, and long-term strategic planning. Storing these data requires a different approach, as the emphasis is on data retention, query flexibility, and cost-effective scalability rather than immediate write and read access. The need to separate real-time data from historical data stems from performance considerations. Real-time data systems prioritize a low latency to ensure that the digital twin is synchronized with the physical infrastructure. In contrast, historical data systems are optimized for cost-effective storage and complex data retrieval operations, which are typically more resource-intensive and can introduce latency if mixed with real-time processing. By maintaining this separation, organizations can ensure that the performance of the digital twin remains unaffected by the intensive computational demands of historical data analysis. External Application Interaction. The architecture we propose streamlines the incorporation of external applications by leveraging a uniform data model and the digital twin's comprehensive representation of the smart grid. In our security-centric approach to safeguarding the smart grid infrastructure, we have adopted OpenSearch, an open-source SIEM (Security Information and Event Management) platform. OpenSearch capitalizes on the standardized data format provided by the digital twin, which is systematically archived within the Kafka broker. This harmonization of data is crucial as it ensures that OpenSearch can efficiently process and analyze information without the need for extensive data normalization procedures. By interfacing directly with the Kafka broker, OpenSearch can access a continuous stream of real-time and historical data, enabling a suite of cybersecurity services that is essential for robust smart grid protection. As highlighted in Figure 1, the services facilitated by OpenSearch include:

* Event Management: OpenSearch aggregates and manages events across the smart grid, providing a centralized view of all activities. This enables operators to monitor the grid's operational status and detect anomalies in real time. * Event Correlation: By correlating disparate events, OpenSearch can identify patterns that may indicate complex cyber threats. This correlation is vital for recognizing multi-stage attacks that single events might not reveal. * Incident Reporting: OpenSearch automates the generation of incident reports, which are critical for compliance with regulatory standards and for initiating appropriate response procedures. * Intrusion Detection: Utilizing advanced analytics and pattern recognition, OpenSearch serves as an intrusion detection system, spotting potential security breaches and alerting operators to take pre-emptive measures. Through the integration of OpenSearch with the digital twin, our architecture not only enhances the security posture of smart grids but also paves the way for advanced analytical capabilities. This integration allows for the proactive management of cybersecurity threats, ensuring the resilience and reliability of energy systems in the face of evolving cyber risks.