Cyber-Resilient Microgrid: Real-time Simulation, Attack Emulation & Secure Monitoring

The increasing digitalization of microgrids introduces new vulnerabilities to cyber-attacks, necessitating robust resilience mechanisms for reliable operation. This paper presents a cyber-resilient microgrid framework integrating real-time simulation, attack emulation, and secure monitoring. The proposed system combines a MATLAB/Simulink-based microgrid model with Linux-based attack emulation tools to simulate realistic threats such as False Data Injection (FDI), Denial-of-Service (DoS), and Man-in-the-Middle (MITM) attacks. Secure communication among distributed controllers is established using Elliptic Curve Cryptography (ECC). A hybrid anomaly detection scheme, merging threshold-based logic and machine learning classification, enhances detection accuracy while reducing false positives. Security events and control actions are immutably logged through a lightweight blockchain for auditability. A React.js dashboard provides real-time visualization, control, and alert management, enabling operators to assess microgrid security and stability dynamically. The integrated architecture demonstrates practical cyber-attack resilience and end-to-end situational awareness for modern smart energy systems.

Keywords: Cyber-resilience, Microgrid, Cyber-attack emulation, Elliptic Curve Cryptography (ECC), Machine learning, Blockchain, Anomaly detection, Real-time simulation, Secure monitoring, MATLAB/Simulink.