# Building Cyber-Resilient Smart Grids with Digital Twins and Data Spaces
## 1 Introduction  
In recent years, the imperative to protect critical infrastructure has become a paramount concern, driven by both industry and academia. As the digital transformation paves the way for more sustainable and efficient services, it simultaneously brings to the fore the essentiality of stringent cybersecurity measures. This is particularly true in the energy sector, where the integration of cyber-physical systems has introduced a spectrum of new security vulnerabilities and safety concerns. The European Commission's introduction of the NIS2 directive [1] marks a significant step towards reinforcing the resilience and defence of these vital systems. In this landscape, the deployment of digital twins has emerged as a crucial strategy for the proactive assessment of cybersecurity risks [2; 3; 4]. These digital replicas of the physical world provide a platform for vigilant monitoring, enabling the early detection and identification of threats as well as the introduction of remediation strategies into critical infrastructure. Digital twins also enable organizations to examine different scenarios, assess the robustness and effectiveness of security measures, and identify areas for improvement. Such a proactive approach is indispensable for shielding critical infrastructures from the dynamic spectrum of the ever-changing landscape of cyber threats. Furthermore, the European Commission has also highlighted the strategic role of common data spaces in achieving data sovereignty, promoting secure data sharing across different sectors, and encouraging stakeholder collaboration [5; 6]. In the energy sector, the establishment of a shared energy data space could lead to improved citizen services and better management systems. Among the different initiatives, FIWARE has emerged as a prominent open-sourceplatform that facilitates the creation of smart applications, ensuring interoperability and fostering an environment of open collaboration [7]. Nonetheless, the Common Information Model (CIM) [8] continues to be the gold standard for data exchange within the power system industry. Bridging the established CIM standard with emerging common data spaces is essential to amplify insights, bolster decision making, and elevate the operational efficiency in the energy sector. This confluence is poised to unlock unprecedented opportunities, catalyze stakeholder cooperation, and accelerate advancements in energy management and service delivery. This paper introduces a framework that leverages the capabilities of FIWARE to tackle the challenge of cybersecurity monitoring in smart power and distribution grids. FIWARE is pivotal in our research, offering a versatile platform that aligns seamlessly with the Common Information Model for smart grid cybersecurity. Its robust support for data spaces and digital twin integration underpins our approach, enhancing interoperability and real-time data analysis. This alignment with FIWARE significantly amplifies the effectiveness of our cybersecurity solutions in smart grid environments. This framework is designed to facilitate the development of data-driven digital twin applications, built upon open-source platforms while maintaining adherence to established industry standards. The ultimate objective is to enhance the cybersecurity monitoring of smart grids through a digital twin that accurately tracks the overall status of the CIM-based architecture of the real system. Enhancing advanced real-time data processing and scalable search capabilities is crucial for efficiently managing and analyzing large-scale, complex datasets in cyber threat detection and response. In our framework, OpenSearch has been integrated to support this activity. Leveraging OpenSearch is necessary in the framework to support the real-time data analysis and scalable search capabilities, essential for smart grid cybersecurity. Its ability to handle complex, voluminous datasets aligns perfectly with the demands of monitoring and protecting smart grid systems.