Construction of Security Attribute Portraits for Power Internet of Things

The insufficiency of current security protection technology for power IoT results in a lack of behavior monitoring and poor security monitoring of terminal access, putting the power system at risk for security risks. In this research, we suggest a technique for building an IoT power terminal security attribute portrait. It can be used as the foundation for terminal trust evaluation in zero-trust architecture. The terminal is monitored and maintained in a multi-dimensional manner by combining the development of three security attribute portraits, and the traffic behavior attributes are categorized using Graph Neural Network (GNN) to improve labeling effects. Finally, we achieve favorable display and application effects for security attributes.