FBIA: A Fog-Based Identity Authentication Scheme for Privacy Preservation in Internet of Vehicles
Author | Song, Liangjun |
Author | Sun, Gang |
Author | Yu, Hongfang |
Author | Du, Xiaojiang |
Author | Guizani, Mohsen |
Available date | 2022-12-09T20:28:58Z |
Publication Date | 2020-05-01 |
Publication Name | IEEE Transactions on Vehicular Technology |
Identifier | http://dx.doi.org/10.1109/TVT.2020.2977829 |
Citation | Song, L., Sun, G., Yu, H., Du, X., & Guizani, M. (2020). Fbia: A fog-based identity authentication scheme for privacy preservation in internet of vehicles. IEEE Transactions on Vehicular Technology, 69(5), 5403-5415. |
ISSN | 00189545 |
Abstract | In recent years, the Internet of vehicles (IoV) has become an indispensable part of wireless communication. To protect users' privacy and communication security, an increasing number of scholars have focused on studying the safety of the IoV. However, due to the characteristics of the IoV, the problem of privacy protection and communication security has not been sufficiently studied and remains open in the IoV; thus, it is worthwhile for us to further explore and study the precise and dynamic safety certification in high-speed driving environments. In our study, we divide the IoV into several fogs to reduce the burden on the traffic control center and propose a new security authentication scheme with the vehicle's identity based on the security elliptic curve. The fog-based identity authentication (FBIA) scheme consists of two layers: the security authentication layer for vehicles outside the fog and the security monitoring layer for the rest of the vehicles. We propose two-way authentication based on the vehicle's identity in the security authentication layer and a deep learning scheme in the security monitoring layer to conduct real-time security in the IoV. Finally, we compare and analyze our FBIA scheme with related approaches, and the results show that the FBIA scheme has higher authentication accuracy and better adaptability to a high-speed mobile network environment in the IoV. |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Internet of vehicles machine learning secure vehicle fog two-way authentication |
Type | Article |
Pagination | 5403-5415 |
Issue Number | 5 |
Volume Number | 69 |
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