微型电脑应用2025，Vol.41Issue(5)：33-37,5.
多尺度加权特征融合下高速公路信息网络安全风险识别
Risk Identification of Highway Information Network Security under Multi-scale Weighted Feature Fusion
摘要
Abstract
The highway information network contains important information of different scales such as traffic flow,accident re-cords and road conditions.Judging risks through a single feature cannot obtain comprehensive information,resulting in limited coverage rate of risk identification.In order to improve the coverage rate of risk identification,a multi-scale weighted feature fusion method for highway information network security risk identification is proposed.The method collects highway informa-tion network data through crawler technology,processes the data by multi-scale weighted feature fusion methods,and establi-shes association rules and risk identification functions based on the feature fusion results to determine the security risks of high-way information data.The experimental results show that the proposed method has a risk identification coverage rate of over 97％,which can complete the risk identification of highway information network,and the identification results are relatively ac-curate.关键词
高速公路信息/爬虫技术/多尺度加权特征融合/关联规则/风险识别Key words
highway information/crawler technology/multi-scale weighted feature fusion/association rule/risk identification分类
信息技术与安全科学引用本文复制引用
陈婧..多尺度加权特征融合下高速公路信息网络安全风险识别[J].微型电脑应用,2025,41(5):33-37,5.基金项目
云南省数字交通重点实验室(202205AG070008) （202205AG070008）
