吉林大学学报（信息科学版）2024，Vol.42Issue(2)：366-371,6.
基于XGBoost算法的内部网络安全威胁检测方法
Threat Detection Method of Internal Network Security Based on XGBoost Algorithm
摘要
Abstract
Aiming at the many causes and difficult features of internal network security threat nodes,an internal network security threat detection method based on XGBoost algorithm is proposed.Using the state differences between the internal network communities as an indicator,the edge weights of the nodes within different community types are calculated to find the nodes associated with the target values.Eigenvalues extracted through multiple assignments are taken as the initial input value XGBoost decision tree to construct the threat feature objective function,solve the corresponding Taylor coefficient of each node,and realize internal network security threat detection.The experimental data show that the proposed method has high feature extraction accuracy and can achieve accurate detection under various network attack conditions.关键词
XGBoost算法/安全威胁检测/目标函数/泰勒系数/网络社区Key words
XGBoost algorithm/security threat detection/objective function/taylor coefficient/network community分类
信息技术与安全科学引用本文复制引用
丁梓轩,陈国..基于XGBoost算法的内部网络安全威胁检测方法[J].吉林大学学报（信息科学版）,2024,42(2):366-371,6.基金项目
江苏省妇幼保健协会科研课题基金资助项目(FYX202201) （FYX202201）
