网络安全与数据治理2026，Vol.45Issue(4)：35-44,10.DOI:10.19358/j.issn.2097-1788.2026.04.005
面向无人机网络攻击检测的两级特征选择方法
A two-stage feature selection method for network attack detection in UAV networks
邓琬巾 1文新 2李维皓 1张玮石 1白猛1
作者信息
- 1. 华北计算机系统工程研究所,北京 100083
- 2. 中国电子信息产业集团有限公司,广东 深圳 518057
- 折叠
摘要
Abstract
To address the dual challenges of high computational demands in machine learning and the limited computing resources of unmanned aerial vehicles(UAVs),as well as the drawback of traditional fixed-binning information gain feature selection methods which underestimate highly discriminative features,this paper proposes a UAV intrusion detection scheme based on a two-level feature selection approach.The scheme adopts a"Chi-square test preliminary screening-Heuristic Information Gain Feature Selection(HIS)fine selection"method,which a-daptively determines the optimal binning for each feature to accurately quantify its discriminative power.Meanwhile,the number of features is treated as a hyperparameter and jointly optimized with the XGBoost classifier.Experiments on the UAV-NIDD dataset demonstrate that the pro-posed method maintains high detection performance while reducing model detection time by approximately 97.5%.The results verify that this scheme effectively balances detection accuracy and computational cost,providing an efficient and real-time intrusion detection capability for re-source-constrained UAV platforms.关键词
无人机/入侵检测/特征选择/信息增益/自适应离散化Key words
UAVs/intrusion detection/feature selection/information gain/adaptive discretization分类
信息技术与安全科学引用本文复制引用
邓琬巾,文新,李维皓,张玮石,白猛..面向无人机网络攻击检测的两级特征选择方法[J].网络安全与数据治理,2026,45(4):35-44,10.
