Fast and Progressive Misbehavior Detection in Internet of Vehicles Based on Broad Learning and Incremental Learning Systems

doi:10.1109/JIOT.2021.3109276

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 平行智能技术与系统团队

	Fast and Progressive Misbehavior Detection in Internet of Vehicles Based on Broad Learning and Incremental Learning Systems
	Wang, Xiao1,2 ; Zhu, Yushan 3; Han, Shuangshuang4 ; Yang, Linyao2,5 ; Gu, Haixia 1; Wang, Fei-Yue2,6,7
发表期刊	IEEE INTERNET OF THINGS JOURNAL
ISSN	2327-4662
	2022-03-15
卷号	9 期号:6 页码:4788-4798
通讯作者	Wang, Xiao(x.wang@ia.ac.cn)
摘要	In recent years, deep learning (DL) has been widely used in vehicle misbehavior detection and has attracted great attention due to its powerful nonlinear mapping ability. However, because of the large number of network parameters, the training processes of these methods are time consuming. Besides, the existing detection methods lack scalability; thus, they are not suitable for Internet of Vehicles (IoV) where new data are constantly generated. In this article, the concept of the broad learning system (BLS) is innovatively introduced into vehicle misbehavior detection. In order to make better use of vehicle information, key features are first extracted from the collected raw data. Then, a BLS is established, which is able to calculate the connection weight of the network efficiently and effectively by ridge regression approximation. Finally, the system can be updated and refined by an incremental learning algorithm based on the newly generated data in IoV. The experimental results show that the proposed method performs much better than DL or traditional classifiers, and could update and optimize the old model fastly and progressively while improving the system's misbehavior detection accuracy.
关键词	Convolutional neural networks Feature extraction Machine learning algorithms Deep learning Global Positioning System Scalability Safety Broad learning system (BLS) incremental learning system Internet of Vehicles (IoV) misbehavior detection ridge regression approximation
DOI	10.1109/JIOT.2021.3109276
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61702519] ; Guangdong Basic and Applied Basic Research Foundation Project[2019B1515120060] ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRI-IACV) ; Science and Technology Development Fund, Macau SAR[0050/2020/A1]
项目资助者	National Natural Science Foundation of China ; Guangdong Basic and Applied Basic Research Foundation Project ; Intel Collaborative Research Institute for Intelligent and Automated Connected Vehicles (ICRI-IACV) ; Science and Technology Development Fund, Macau SAR
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000766683600063
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	人工智能+交通
引用统计	被引频次：21[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/173211/47964
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
通讯作者	Wang, Xiao
作者单位	1.China Nucl Power Engn Co Ltd, State Key Lab Nucl Power Safety Monitoring Techno, Shenzhen 518172, Guangdong, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100080, Peoples R China 3.Zhejiang Univ, Sch Comp Sci, Hangzhou 310027, Peoples R China 4.Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 6.Natl Univ Def Technol, Res Ctr Mil Computat Expt & Parallel Syst Technol, Changsha 410073, Peoples R China 7.Macau Univ Sci Technol, Inst Syst Engn, Macau, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Wang, Xiao,Zhu, Yushan,Han, Shuangshuang,et al. Fast and Progressive Misbehavior Detection in Internet of Vehicles Based on Broad Learning and Incremental Learning Systems[J]. IEEE INTERNET OF THINGS JOURNAL,2022,9(6):4788-4798.
APA	Wang, Xiao,Zhu, Yushan,Han, Shuangshuang,Yang, Linyao,Gu, Haixia,&Wang, Fei-Yue.(2022).Fast and Progressive Misbehavior Detection in Internet of Vehicles Based on Broad Learning and Incremental Learning Systems.IEEE INTERNET OF THINGS JOURNAL,9(6),4788-4798.
MLA	Wang, Xiao,et al."Fast and Progressive Misbehavior Detection in Internet of Vehicles Based on Broad Learning and Incremental Learning Systems".IEEE INTERNET OF THINGS JOURNAL 9.6(2022):4788-4798.