The high uncertainty and randomness are the characteristics of the sensor data in the Cyber-Physical Systems (CPS), which make the data unreliable. A creditability analysis framework is proposed to solve those problems. Abandoning the idea that the sensor is the center in modeling, the theory takes monitoring targets into consideration and constructs the sensor-target relationship diagram, which is the base of the creditability reasoning algorithm. Meanwhile, in order to reduce the space and time of searching the relationship diagram, an improving reasoning method basing on filtering the incredible targets is designed. The examples demonstrate that the proposed algorithm can filter out the false message in the sensor data and enhances the creditability of the data in CPS.
汤巍, 景博, 黄以锋. 基于关联图模型的信息物理融合系统感知数据可信性分析[J]. 电子与信息学报, 2015, 37(3): 679-685.
Tang Wei, Jing Bo, Huang Yi-Feng. Creditability Analysis of Sensor Data in the Cyber-physical System Based on the Relationship Diagram Model. JEIT, 2015, 37(3): 679-685.