福建电脑2024，Vol.40Issue(5)：6-13,8.DOI:10.16707/j.cnki.fjpc.2024.05.002
布隆过滤器优化的高效车联网入侵检测技术
Bloom Filter Optimized High-efficiency Internet of Vehicles Intrusion Detection Technology
摘要
Abstract
To address the shortcomings of real-time detection efficiency and accuracy in vehicle networking intrusion detection systems,this paper proposes an intrusion detection system mechanism BFET-IDS based on Bloom filters.Firstly,a Bloom filter is used to optimize data search and spatial utilization,followed by a tree structure algorithm for fast feature extraction and real-time detection.The experimental results show that the BFET-IDS model achieves a fast detection of 17.17 microseconds while achieving a high accuracy.关键词
布隆过滤/机器学习/入侵检测/车联网Key words
Bloom Filtering/Machine Learning/Intrusion Detection/Internet of Vehicles分类
信息技术与安全科学引用本文复制引用
张章学..布隆过滤器优化的高效车联网入侵检测技术[J].福建电脑,2024,40(5):6-13,8.基金项目
本文得到福建省交通厅科技项目"智慧交通网络安全运行监测调度关键技术研究"(No.2022Y139)资助. （No.2022Y139）
