COVID-19 Vehicle Based on an Efficient Mutual Authentication Scheme for 5G-Enabled Vehicular Fog Computing

被引:35
作者
Al-Shareeda, Mahmood A. [1 ]
Manickam, Selvakumar [1 ]
机构
[1] Univ Sains Malaysia, Natl Adv IPv6 Ctr NAv6, George Town 11800, Penang, Malaysia
关键词
COVID-19; vehicle; fog server; 5G-enabled vehicular network; authentication; PRIVACY; PROTOCOL; PLUS;
D O I
10.3390/ijerph192315618
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The COVID-19 pandemic is currently having disastrous effects on every part of human life everywhere in the world. There have been terrible losses for the entire human race in all nations and areas. It is crucial to take good precautions and prevent COVID-19 because of its high infectiousness and fatality rate. One of the key spreading routes has been identified to be transportation systems. Therefore, improving infection tracking and healthcare monitoring for high-mobility transportation systems is impractical for pandemic control. In order to enhance driving enjoyment and road safety, 5G-enabled vehicular fog computing may gather and interpret pertinent vehicle data, which open the door to non-contact autonomous healthcare monitoring. Due to the urgent need to contain the automotive pandemic, this paper proposes a COVID-19 vehicle based on an efficient mutual authentication scheme for 5G-enabled vehicular fog computing. The proposed scheme consists of two different aspects of the special flag, SF = 0 and SF = 1, denoting normal and COVID-19 vehicles, respectively. The proposed scheme satisfies privacy and security requirements as well as achieves COVID-19 and healthcare solutions. Finally, the performance evaluation section shows that the proposed scheme is more efficient in terms of communication and computation costs as compared to most recent related works.
引用
收藏
页数:16
相关论文
共 41 条
[41]   Edge Computing-Based Privacy-Preserving Authentication Framework and Protocol for 5G-Enabled Vehicular Networks [J].
Zhang, Jing ;
Zhong, Hong ;
Cui, Jie ;
Tian, Miaomiao ;
Xu, Yan ;
Liu, Lu .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (07) :7940-7954