基于布谷鸟算法的实验室网络入侵数据检测  

Laboratory Network Intrusion Data Detection Based on Cuckoo Bird Algorithm

作　　者：闫培玲 刘俊娟[1] YAN Pei-ling;LIU Jun-juan(Henan University of Chinese Medicine,School of Information Technology,Zhengzhou Henan 450046,China)

机构地区：[1]河南中医药大学信息技术学院,河南郑州450046

出　　处：《计算机仿真》2025年第3期448-451,456,共5页Computer Simulation

基　　金：全国高等院校计算机基础教育研究会计算机基础教育教学研究项目(2023-AFCEC-243);河南中医药大学2022年度科研苗圃工程项目(MP2022-22);教育部产学合作协同育人项目(231100440174038)。

摘　　要：实验室网络具有高速数据传输要求且存在大量的网络节点,受复杂、隐蔽的网络威胁影响,使得实验室网络数据的入侵检测能力降低。为此,提出一种基于布谷鸟算法的实验室网络入侵数据检测方法。将正则化回归模型和半监督等距映射数据降维方法两者有效结合,降维处理实验室网络数据。提取实验室网络入侵数据特征,通过大数据信息融合以及关联规则挖掘方法,检测实验室网络入侵数据。引入布谷鸟算法,对实验室网络入侵数据检测过程自适应寻优,实现入侵检测优化。通过仿真分析证明,所提方法可以有效提升实验室网络入侵数据检测结果准确性,检测率在97%以上,减少检测时间。The laboratory network requires high-speed data transmission and has a large number of network nodes.Due to complex and covert network threats,the intrusion detection capability of laboratory network data is reduced.As a result,this article presented a method of detecting laboratory network intrusion data based on cuckoo algorithm.Firstly,the regularized regression model was effectively combined with the method of semi-supervised isometric mapping data dimensionality reduction to reduce the dimension of laboratory network data.Then,the features of laboratory network intrusion data were extracted.Moreover,big data information fusion and association rule mining methods were used to detect the intrusion data.Finally,the cuckoo algorithm was introduced to adaptively optimize the detection process of laboratory network intrusion data,thus realizing the detection optimization.The simulation analysis shows that the proposed method can effectively improve the accuracy of laboratory network intrusion data detection result and reduce detection time.Its detection rate is over 97%.

关 键 词：布谷鸟算法 实验室网络 入侵数据 检测 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]