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基于被动分簇算法的无线通信网络漏洞深度挖掘方法

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无线通信网络漏洞类型复杂,传统方法难以准确同时检测不同类型的漏洞,为此提出基于被动分簇算法的无线通信网络漏洞深度挖掘方法.采用基于被动分簇的网关节点计算方法,在网络出现通信需求时,通过被动式分簇算法设置簇头,遵循网络健壮性和能量有效性间的均衡原则,明确网关节点.使用基于信息熵的异常网关节点聚类筛选机制,锁定网络中异常网关节点,通过基于自回归模型的漏洞节点深度挖掘方法,在异常网关节点所连接簇头的管辖范围中,结合漏洞判断阈值条件,识别存在漏洞的底层普通节点,实现无线通信网络漏洞深度挖掘.实验结果表明,该方法可在0.3 s之内完成无线通信网络漏洞深度挖掘,且挖掘结果准确无误.
Deep Mining Method for Wireless Communication Network Vulnerability Based on Passive Clustering Algorithm
The types of vulnerabilities in wireless communication networks are complex,and traditional methods are difficult to accurately detect different types of vulnerabilities simultaneously.Therefore,a deep mining method for wireless communication network vulnerability based on passive clustering algorithm is proposed.This paper adopts gateway node calculation method based on passive clustering.When there is a communication demand in the network,the cluster head is set through the passive clustering algorithm,following the principle of balancing network robustness and energy efficiency to clarify the gateway nodes.It uses the clustering and filtering mechanism for abnormal gateway nodes based on information entropy to lock the abnormal gateway nodes in the network.Through a vulnerability node deep mining method based on autoregressive models,it identifies the underlying ordinary nodes within the jurisdiction of the cluster heads connected to the abnormal network nodes,combined with vulnerability judgment threshold conditions,so as to achieve deep mining in wireless communication network vulnerability.The experimental results show that this method can complete deep mining of wireless communication network vulnerability within 0.3 seconds,and the mining results are accurate.

passive clustering algorithmwireless communicationnetwork vulnerabilitydeep miningcluster head nodegateway node

伍慧怡、梁焕桢、陈虹安、梁炎新、吕松松、郑欣健

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广东江门幼儿师范高等专科学校,广东 江门 529000

江门职业技术学院,广东 江门 529090

被动分簇算法 无线通信 网络漏洞 深度挖掘 簇头节点 网关节点

2024

现代信息科技
广东省电子学会

现代信息科技

ISSN:2096-4706
年,卷(期):2024.8(17)