摘要
针对远距离传输和集中式处理方式带来的问题,为降低密集传感节点入侵任务检测的难度,减少时延开销和网络负荷,进一步消除隐私泄露风险,利用更靠近传感网络节点的移动边缘计算的明显优势,提出一种基于移动边缘计算和SSA算法的无线传感网络入侵检测方法。通过将有计算能力的边缘服务器部署于靠近传感节点的位置,采集无线传感网络数据并提取网络安全特征,大幅缩短采集时间。通过麻雀搜索算法调整节点采集中的搜索策略,结合梯度变化降维避免陷入最优,以普通节点位置和节点特征为依据,进行分布式入侵检测,实现无线传感网络的入侵检测。实验证明:本方法节点入侵检测平均准确率达98.52%,检测平均延时为1.67 ms,具有出色的应用性能。
Aiming at the problems caused by long-distance transmission and centralized processing,in order to reduce the difficulty of intrusion detection of dense sensor nodes,reduce the delay overhead and network load,and further eliminate the risk of privacy leakage,a wireless sensor network intrusion detection method based on mobile edge computing and SSA algorithm is proposed by taking advantage of the obvious advantages of mobile edge computing closer to sensor network nodes.By deploying the edge server with computing ability near the sensor nodes,the data of wireless sensor networks are collected and the network security features are extracted,which greatly shortens the collection time.The sparrow search algorithm is used to adjust the search strategy in node collection,and the gradient change is combined to reduce the dimension to avoid falling into the optimum.Based on the location and characteristics of common nodes,distributed intrusion detection is carried out to realize the intrusion detection of wireless sensor networks.Experiments show that the average accuracy of node intrusion detection is 98.52%,and the average detection delay is 1.67 ms,so it has excellent application performance.
作者
刘科迪
刘静
LIU Kedi;LIU Jing(School of Computer Science and Technology,Wuhan University of Science and Technology,Wuhan 430081,China)
出处
《微处理机》
2024年第2期26-30,共5页
Microprocessors
关键词
移动边缘计算
麻雀搜索算法
无线传感网络
入侵检测
特征提取
Mobile edge computing
Sparrow search algorithm
Wireless sensor network
Intrusion detection
Feature extraction
