城市物联网采集数据可信度量机制研究OA

The diversity,heterogeneity,and wide distribution characteristics of IoT devices expose their operational processes to risks such as data source forgery or tampering in sensing devices.However,current trust evaluation models in multi-domain IoT scenarios for smart cities exhibit limited dynamic adaptability and lack comprehensive capabilities in addressing security threats.To address these issues,this study proposes a framework from the macro-operational perspective of IoT,integrating trusted computing technologies.We construct static attribute metrics and dynamic attribute metrics mechanisms for IoT device nodes,categorize trust levels by employing clustering algorithms,and establish a comprehensive trusted metrics mechanism tailored for multi-source heterogeneous IoT devices.Subsequently,through simulation experiments based on a multi-domain distributed IoT architecture,we validate that the proposed trusted metrics scheme effectively detects initial malicious propagation by malicious nodes,confines malicious propagation within a limited scope,and robustly addresses security challenges under varying proportions of malicious nodes.