Construction of a hierarchical classification and hierarchical security control system for multi-source, affordable data in smart grids

Introduction: To create an integrated hierarchical classification and hierarchical security control system to enhance real-time decision-making and protection in smart-grid contexts, Smart grids produce high-volume, heterogeneous multi-source data (smart meters, sensors, control systems) and are becoming more vulnerable to cyber threats. Method: The paper has provided hierarchical classification and security control system to manage multi-source data in smart grids. The system combines smart meter, sensor and control system data and allows the efficient real time decision making. The framework categorizes multi-source data into priority levels based on Decision Tree and Random Forest models and implements a multi-layer security control mechanism with real-time monitoring, anomaly detection, and response measures based on the classification result. A multi-layered security control framework is established to counter the cyber threats, and real-time monitoring mechanisms, anomaly detection mechanisms and response mechanisms are established. Results: The experimental findings demonstrate a high level of performance with an accuracy of 96.25, a precision of 97.49, a recall of 94.87 and an F1-score of 95.30. The system also guarantees a steady response time of 1.6 seconds on critical and non-critical threats, but there are scalability concerns with the system responding more slowly to both critical and non-critical threats (detected threats are lost when scaling to more than 5,000 devices). Conclusions: The results identify the high efficiency of the framework in offering secure, efficient, and scalable smart grid management solutions..