基于图神经网络的物联网入侵检测研究OA
Research on Intrusion Detection of Internet of Things Based on Graph Neural Network
针对物联网入侵检测中网络设备的异构性以及设备间的复杂关联性,本文基于图神经网络(Graph Neural Network,GNN)提出一种GraphSAGE-GAT模型,可以有效捕捉物联网设备之间的关联关系,并还原物联网设备之间的通信拓扑,从而达到提升物联网异常检测准确率的目的.首先,基于物联网设备间的网络流数据构建了设备关联关系图,然后利用GraphSAGE(Graph Sample and Aggregate)算法对相邻设备节点进行采样,从而…查看全部>>
Aiming at the heterogeneity of network devices and the complex correlation among devices in the internet of things intrusion detection,this paper proposed a GraphSAGE-GAT model based on the graph neural network,which could effectively capture the correlation between internet of things devices and reduced the communication topology between internet of things devices,so as to improve the accuracy rate of internet of things anomaly detection.Firstly,the device …查看全部>>
李聪宇;赵利辉;安洋
中北大学 软件学院, 山西 太原 030051中北大学 软件学院, 山西 太原 030051中北大学 软件学院, 山西 太原 030051
计算机与自动化
物联网入侵检测特征选择GraphSAGE图注意力网络
internet of thingsintrusion detectionfeature selectiongraph sample and aggregate(Graph-SAGE)graph attention network
《中北大学学报（自然科学版）》 2024 (2)
194-204,11
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