A Many-Objective Optimization Based Intelligent Intrusion Detection Algorithm for Enhancing Security of Vehicular Networks in 6G

doi:10.1109/TVT.2021.3057074

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 人工智能与机器学习（杨雪冰）-技术团队

	A Many-Objective Optimization Based Intelligent Intrusion Detection Algorithm for Enhancing Security of Vehicular Networks in 6G
	Zhang, Zhixia 1,2; Cao, Yang 3; Cui, Zhihua 4; Zhang, Wensheng5 ; Chen, Jinjun 6
发表期刊	IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
ISSN	0018-9545
	2021-06-01
卷号	70 期号:6 页码:5234-5243
通讯作者	Cui, Zhihua(cuizhihua@tyust.edu.cn)
摘要	With accelerated ensemble of the Internet of Things technology and automotive industry, vehicular network has been established as powerful tools. However, it is a significant challenge for dynamic and heterogeneous vehicular network to meet high requirements of the sixth-generation (6G) network such as high reliability and high security. To address this challenge, we design a novel weight-based ensemble machine learning algorithm (WBELA) to identify abnormal messages of vehicular Controller Area Network (CAN) bus network. Then, we establish a model based on many-objective optimization for intrusion detection of CAN bus network. To support this model, a many-objective optimization algorithm based on balance convergence and diversity (MaOEA-BCD) is designed. Open-source CAN bus message data sets and tamper attack scenarios are used to evaluate the effectiveness of proposed algorithm for different ID data frames. Experimental results revealed that proposed methods significantly enhance precision, reduce the false positive rate and have better performance than other methods so as to enhance security of vehicular networks in 6G.
关键词	Intrusion detection Security 6G mobile communication Data models Protocols Optimization Encryption Controller area network (CAN) intrusion detection machine learning (ML) many-objective optimization vehicular networks security
DOI	10.1109/TVT.2021.3057074
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China[2018YFC1604000] ; National Natural Science Foundation of China[61 806 138] ; National Natural Science Foundation of China[61 772 478] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61961160707] ; National Natural Science Foundation of China[61 976 212] ; Key R&D program of Shanxi Province (HighTechnology)[201903D121119] ; Key R&D program of Shanxi Province (International Cooperation)[201903D421048] ; Postgraduate Education Innovation Project of Shanxi Province[2020SY437] ; Natural Science Foundation of Shanxi Province[201801D121127] ; Australian Research Council (ARC)[DP190101893] ; Australian Research Council (ARC)[DP170100136] ; Australian Research Council (ARC)[LP180100758]
项目资助者	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key R&D program of Shanxi Province (HighTechnology) ; Key R&D program of Shanxi Province (International Cooperation) ; Postgraduate Education Innovation Project of Shanxi Province ; Natural Science Foundation of Shanxi Province ; Australian Research Council (ARC)
WOS研究方向	Engineering ; Telecommunications ; Transportation
WOS类目	Engineering, Electrical & Electronic ; Telecommunications ; Transportation Science & Technology
WOS记录号	WOS:000671544000005
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：62[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/45259
专题	多模态人工智能系统全国重点实验室_人工智能与机器学习（杨雪冰）-技术团队
通讯作者	Cui, Zhihua
作者单位	1.Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Sch Elect Informat Engn, Taiyuan 030024, Shanxi, Peoples R China 2.Taiyuan Univ Sci & Technol, Shanxi Key Lab Adv Control & Equipment Intelligen, Taiyuan 030024, Shanxi, Peoples R China 3.Beijing Wuzi Univ, Sch Informat, Beijing 101149, Peoples R China 4.Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Taiyuan 030024, Shanxi, Peoples R China 5.Chinese Acad Sci, State Key Lab Intelligent Control & Management Co, Inst Automat, Beijing 100190, Peoples R China 6.Swinburne Univ Technol, Melbourne, Vic 3000, Australia
推荐引用方式 GB/T 7714	Zhang, Zhixia,Cao, Yang,Cui, Zhihua,et al. A Many-Objective Optimization Based Intelligent Intrusion Detection Algorithm for Enhancing Security of Vehicular Networks in 6G[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,2021,70(6):5234-5243.
APA	Zhang, Zhixia,Cao, Yang,Cui, Zhihua,Zhang, Wensheng,&Chen, Jinjun.(2021).A Many-Objective Optimization Based Intelligent Intrusion Detection Algorithm for Enhancing Security of Vehicular Networks in 6G.IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY,70(6),5234-5243.
MLA	Zhang, Zhixia,et al."A Many-Objective Optimization Based Intelligent Intrusion Detection Algorithm for Enhancing Security of Vehicular Networks in 6G".IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 70.6(2021):5234-5243.