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Abstract
This paper analyzes the current real‐time monitoring system based on grey‐related IoT security sensors for the detection of risk factors in the production environment of the Internet of Things and proposes a design plan for the Internet of Things environment monitoring based on the grey‐related Internet of Things security sensor network, and according to the reliability guarantee mechanism of the system, a three‐dimensional uniform IoT node deployment method suitable for IoT security monitoring is proposed. Based on the grey correlation analysis, it can provide a quantitative measurement analysis for the development and change state of a system, which is very suitable for the analysis of dynamic operating systems. As a real‐time dynamic system of the Internet of Things, the use of grey correlation method to analyze its network security status has good operability and practical value. According to the multisource information processing technology, the monitoring data are preprocessed by dynamic limiting filtering, and then the data are fused at the data level with the optimal weighting algorithm. Through the use of grey correlation analysis to quantify the relative impact of cyberattacks on the network within a certain period of time, the quantitative assessment of the security environment and status of the entire network is realized. Finally, the characteristics of grey relational analysis and rough set theory attribute reduction are used to form the basis of grey correlation decision‐level fusion algorithm, to achieve effective processing of the data of the Internet of Things security monitoring system.
Highlights
Real-time monitoring of the operating environment of the Internet of ings is one of the important means to prevent the occurrence of Internet of ings accidents and improve the safety management of the Internet of ings [1]
In China, many types of Internet of ings are still monitored by traditional wired methods [3]. e grey relational Internet of ings security sensor network technology is widely used in monitoring systems [4]. erefore, most of the domestic Internet of ings is a wired monitoring system, and the technical approach is active FIRD combined with communication methods such as Ethernet [5]
IoT node deployment parts: task management platform, mobility management platform, and energy management platform. e distance that can be monitored by the two basic monitoring planes is as follows: when the basic monitoring planes are arranged in sequence, there are IoT security sensor nodes in each horizontal row, the entire distance is divided into n uniform parts, and the length of each part is the sensing radius of the security sensor of the Internet of ings, so the distance that can be monitored by deploying the basic monitoring surface is x(n) xi, i 1, 2, . . . , n
Summary
Internet of Things Security Detection Technology Based on Grey Association Decision Algorithm. As a real-time dynamic system of the Internet of ings, the use of grey correlation method to analyze its network security status has good operability and practical value. According to the multisource information processing technology, the monitoring data are preprocessed by dynamic limiting filtering, and the data are fused at the data level with the optimal weighting algorithm. The characteristics of grey relational analysis and rough set theory attribute reduction are used to form the basis of grey correlation decision-level fusion algorithm, to achieve effective processing of the data of the Internet of ings security monitoring system
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