Analysis of Recent Deep-Learning-Based Intrusion Detection Methods for In-Vehicle Network
Author:
Affiliation:
1. School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China
2. Big Data Center, State Grid Corporation of China, Beijing, China
Funder
National Natural Science Foundation of China
Double First-Class Scientific Research Funds of HIT
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/4358928/09963783.pdf?arnumber=9963783
Reference27 articles.
1. Cybersecurity for autonomous vehicles: Review of attacks and defense
2. Survey on artificial intelligence (AI) techniques for vehicular ad-hoc networks (VANETs);mchergui;Veh Commun,2021
3. A survey on Intrusion Detection Systems and Honeypot based proactive security mechanisms in VANETs and VANET Cloud
4. A Survey of Intrusion Detection for In-Vehicle Networks
5. Guest Editorial Introduction to the Special Issue on Deep Learning Models for Safe and Secure Intelligent Transportation Systems
Cited by 22 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Deep learning based network intrusion detection system: a systematic literature review and future scopes;International Journal of Information Security;2024-08-02
2. A Lightweight Intrusion Detection System Using a Finite Dirichlet Mixture Model With Extended Stochastic Variational Inference;IEEE Transactions on Network and Service Management;2024-08
3. ECF-IDS: An Enhanced Cuckoo Filter-Based Intrusion Detection System for In-Vehicle Network;IEEE Transactions on Network and Service Management;2024-08
4. Deep learning-empowered intrusion detection framework for the Internet of Medical Things environment;Knowledge and Information Systems;2024-06-10
5. Finding Component Relationships: A Deep-Learning-Based Anomaly Detection Interpreter;IEEE Transactions on Computational Social Systems;2024-06
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3