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Status已发表Published
TitleCluster-Based Malicious Node Detection for False Downstream Data in Fog Computing-Based VANETs
Creator
Date Issued2022
Source PublicationIEEE Transactions on Network Science and Engineering
ISSN2327-4697
Volume9Issue:3Pages:1245-1263
Abstract

In this paper, we propose a cluster-based malicious node detection scheme for false downstream data in fog computing-based VANETs, where the fog servers are used to detect the suspicious data and the malicious cluster head nodes. In our proposed scheme, we further construct a trajectory clustering method among vehicle nodes, in which the cluster head nodes and the corresponding edge monitoring nodes are accurately selected. Also, under our proposed threat model, we analyze the potential security problems in detail. Compared with other related works, our proposed detection scheme can supervise the downstream data forwarded by the cluster head nodes and detect the malicious cluster head nodes. Further, the experimental results show our proposed scheme is efficient for fog computing-based VANETs. Therefore, our scheme may be used as an auxiliary mechanism of some cryptography-based schemes not only to ensure the security of the data forwarding process, but also to effectively and timely monitor the data forwarding process.

KeywordCluster Cryptography False downstream data Fog computing Malicious node detection Monitoring Reliability Routing Security Servers Trajectory VANET
DOI10.1109/TNSE.2021.3139005
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaEngineering ; Mathematics
WOS SubjectEngineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS IDWOS:000800200900028
Scopus ID2-s2.0-85122582305
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/8282
CollectionFaculty of Science and Technology
Affiliation
1.School of Computer and Communication Engineering, Changsha University of Science and Technology, 12418 Changsha, Hunan, China, 410114 (e-mail: gk4572@163.com)
2.School of Computer and Communication Engineering, Changsha University of Science and Technology - Yuntang Campus, 12418 Changsha, Hunan, China, (e-mail: 296014320@qq.com)
3.School of Computer Science and Engineering, University of Electronic Science and Technology of China, 12599 Chengdu, Sichuan, China, 610054 (e-mail: lixiongzhq@163.com)
4.Department of Computer and Information Science, Beijing Normal University-Hong Kong Baptist University United International College, 125809 Zhuhai, Guangdong, China, (e-mail: jiawei_1950@hotmail.com)
Recommended Citation
GB/T 7714
Gu, Ke,Dong, Xinying,Li, Xionget al. Cluster-Based Malicious Node Detection for False Downstream Data in Fog Computing-Based VANETs[J]. IEEE Transactions on Network Science and Engineering, 2022, 9(3): 1245-1263.
APA Gu, Ke, Dong, Xinying, Li, Xiong, & Jia, Weijia. (2022). Cluster-Based Malicious Node Detection for False Downstream Data in Fog Computing-Based VANETs. IEEE Transactions on Network Science and Engineering, 9(3), 1245-1263.
MLA Gu, Ke,et al."Cluster-Based Malicious Node Detection for False Downstream Data in Fog Computing-Based VANETs". IEEE Transactions on Network Science and Engineering 9.3(2022): 1245-1263.
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