Intelligent Monitoring System for IoT Network Cards Based on Graph Neural Network and XGBoost Model
With the rapid development of IoT service,the complex and diverse application scenarios have brought huge challenges to the operation and management of IoT network cards,and traditional management methods are no longer able to meet the regula-tory requirements for the use of IoT network cards.Firstly,it summarizes the current situation and management methods of abnormal usage of IoT network cards,analyzes the shortcomings of existing recognition methods for abnormal use of IoT net-work cards,and proposes a method for IoT network card profile feature fusion construction based on graph neural network(GNN)and Count-Min Sketch algorithm,and the abnormal traffic recognition model based on XGBoost algorithm.Based on the above technologies,an intelligent monitoring system for IoT network cards has been implemented,which improves the precision and recall of abnormal behavior recognition.
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