Security Detection Method for Clustering Wireless Sensor Networks Based on Markov Chain

被引:0
|
作者
Dong, Na [1 ]
Chen, Ze [1 ]
Liu, Weina [1 ]
Hou, Botao [1 ]
机构
[1] Power Grid Technology Center, State Grid Hebei Electric Power Research Institute, Shijiazhuang,050000, China
来源
Engineering Intelligent Systems | 2022年 / 30卷 / 01期
关键词
Feature extraction - Markov processes - Network security - Phase space methods - Sensor nodes - Transmissions;
D O I
暂无
中图分类号
学科分类号
摘要
In order to improve the mining and intelligent analysis capability of the transmission information of clustered wireless sensor networks, a security detection method for transmission information of clustered wireless sensor networks based on Markov chain is proposed. This involves constructing a distributed sensing sequence sampling model of clustered wireless sensor network transmission information, reconstructing association rule feature quantities of clustered wireless sensor network transmission information obtained by sensing detection, establishing a Markov chain information mining model of clustered wireless sensor network transmission information, adopting a wireless sensor network information fusion tracking identification method, carrying out adaptive fusion and feature clustering of clustered wireless sensor network transmission information. Combined with the phase space reconstruction method, the discrete fusion processing of the transmission information of the clustered wireless sensor network is carried out, and the correlation spectrum feature extraction is carried out on the transmission information of the clustered wireless sensor network in the routing relay node, so that the safety detection of the transmission information of the clustered wireless sensor network is realized. The simulation results show that this method has higher accuracy, better security and a higher level of fusion for the transmission information detection of clustered wireless sensor networks as well as good security detection and feature analysis capabilities for clustered wireless sensor networks. © 2022 CRL Publishing. All rights reserved.
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页码:55 / 65
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