Status | 已发表Published |
Title | Cluster-Based Malicious Node Detection for False Downstream Data in Fog Computing-Based VANETs |
Creator | |
Date Issued | 2022 |
Source Publication | IEEE Transactions on Network Science and Engineering
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ISSN | 2327-4697 |
Volume | 9Issue: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. |
Keyword | Cluster Cryptography False downstream data Fog computing Malicious node detection Monitoring Reliability Routing Security Servers Trajectory VANET |
DOI | 10.1109/TNSE.2021.3139005 |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Engineering ; Mathematics |
WOS Subject | Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications |
WOS ID | WOS:000800200900028 |
Scopus ID | 2-s2.0-85122582305 |
Citation statistics | |
Document Type | Journal article |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/8282 |
Collection | Faculty 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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