IoT Terminal Security Monitoring and Assessment Model Relying on Grey Relational Cluster Analysis

Abstract

IoT (Internet of Things) terminal security monitoring and evaluation encompasses technique and administration. There are several uncertainties in the monitoring and assessment process of various types of IoT terminals, which cannot be fully quantified. Therefore, it is difficult to achieve completely objective safety risk evaluation. For this to happen, the study proposes an IoT terminal security monitoring and assessment model based on grey relational cluster analysis. First, by integrating experts’ knowledge, the conditional probability matrix (CPM) of cluster analysis are explained, which lays the foundation for establishing the security monitoring and assessment model. Then, through the grey relational cluster algorithm, the subjective judgment information of the experts on the threat degree of the target information system is synthesized as prior information. At the same time, through the observation node of objective evaluation information, the safety threat levels are synergized to realize the continuity and accumulation of safety evaluation. Ultimately, simulation examples verify the rationality and effectiveness of the pattern.