IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i23p15618-d983195.html
   My bibliography  Save this article

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

Author

Listed:
  • Mahmood A. Al-Shareeda

    (National Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, George Town 11800, Penang, Malaysia)

  • Selvakumar Manickam

    (National Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, George Town 11800, Penang, Malaysia)

Abstract

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.

Suggested Citation

  • Mahmood A. Al-Shareeda & Selvakumar Manickam, 2022. "COVID-19 Vehicle Based on an Efficient Mutual Authentication Scheme for 5G-Enabled Vehicular Fog Computing," IJERPH, MDPI, vol. 19(23), pages 1-16, November.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15618-:d:983195
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/23/15618/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/23/15618/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sun, Xiaoqian & Wandelt, Sebastian & Zheng, Changhong & Zhang, Anming, 2021. "COVID-19 pandemic and air transportation: Successfully navigating the paper hurricane," Journal of Air Transport Management, Elsevier, vol. 94(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zeyad Ghaleb Al-Mekhlafi & Mahmood A. Al-Shareeda & Selvakumar Manickam & Badiea Abdulkarem Mohammed & Amjad Qtaish, 2023. "Lattice-Based Lightweight Quantum Resistant Scheme in 5G-Enabled Vehicular Networks," Mathematics, MDPI, vol. 11(2), pages 1-17, January.
    2. Phon Sheng Hou & Lokman Mohd Fadzil & Selvakumar Manickam & Mahmood A. Al-Shareeda, 2023. "Vector Autoregression Model-Based Forecasting of Reference Evapotranspiration in Malaysia," Sustainability, MDPI, vol. 15(4), pages 1-18, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Garaus, Marion & Hudáková, Melánia, 2022. "The impact of the COVID-19 pandemic on tourists’ air travel intentions: The role of perceived health risk and trust in the airline," Journal of Air Transport Management, Elsevier, vol. 103(C).
    2. Morlotti, Chiara & Redondi, Renato, 2023. "The impact of COVID-19 on airlines’ price curves," Journal of Air Transport Management, Elsevier, vol. 107(C).
    3. Tuchen, Stefan & Nazemi, Mohsen & Ghelfi-Waechter, Signe Maria & Kim, Euiyoung & Hofer, Franziska & Chen, Ching-Fu & Arora, Mohit & Santema, Sicco & Blessing, Lucienne, 2023. "Experiences from the international frontlines: An exploration of the perceptions of airport employees during the COVID-19 pandemic," Journal of Air Transport Management, Elsevier, vol. 109(C).
    4. Huimin Liu & Yupeng Shi & Xuze Yang & Wentao Zhang, 2023. "The Role of Business Environment and Digital Government in Mitigating Supply Chain Vulnerability—Evidence from the COVID-19 Shock," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    5. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2021. "Technological and educational challenges towards pandemic-resilient aviation," Transport Policy, Elsevier, vol. 114(C), pages 104-115.
    6. Thitinan Pholsook & Warit Wipulanusat & Poomporn Thamsatitdej & Sarawut Ramjan & Jirapon Sunkpho & Vatanavongs Ratanavaraha, 2023. "A Three-Stage Hybrid SEM-BN-ANN Approach for Analyzing Airport Service Quality," Sustainability, MDPI, vol. 15(11), pages 1-20, May.
    7. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2021. "Vaccination passports: Challenges for a future of air transportation," Transport Policy, Elsevier, vol. 110(C), pages 394-401.
    8. Hong, Seock-Jin & Savoie, Michael & Joiner, Steve & Kincaid, Timothy, 2022. "Analysis of airline employees’ perceptions of corporate preparedness for COVID-19 disruptions to airline operations," Transport Policy, Elsevier, vol. 119(C), pages 45-55.
    9. Xue, Dabin & Liu, Zhizhao & Wang, Bing & Yang, Jian, 2021. "Impacts of COVID-19 on aircraft usage and fuel consumption: A case study on four Chinese international airports," Journal of Air Transport Management, Elsevier, vol. 95(C).
    10. Mutascu, Mihai & Sokic, Alexandre, 2023. "Air transportation under COVID-19 pandemic restrictions: A wavelet analysis," Transport Policy, Elsevier, vol. 139(C), pages 155-181.
    11. Li, Tao & Rong, Lili, 2021. "Impacts of service feature on vulnerability analysis of high-speed rail network," Transport Policy, Elsevier, vol. 110(C), pages 238-253.
    12. Zhang, Linfeng & Yang, Hangjun & Wang, Kun & Bian, Lei & Zhang, Xian, 2021. "The impact of COVID-19 on airline passenger travel behavior: An exploratory analysis on the Chinese aviation market," Journal of Air Transport Management, Elsevier, vol. 95(C).
    13. Xiaoqian Sun & Sebastian Wandelt & Hartmut Fricke & Judith Rosenow, 2021. "The Impact of COVID-19 on Air Transportation Network in the United States, Europe, and China," Sustainability, MDPI, vol. 13(17), pages 1-11, August.
    14. Li, Tao & Rong, Lili & Zhang, Anming, 2021. "Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail," Transport Policy, Elsevier, vol. 106(C), pages 226-238.
    15. Kim, Myeonghyeon & Sohn, Jeongwoong, 2022. "Passenger, airline, and policy responses to the COVID-19 crisis: The case of South Korea," Journal of Air Transport Management, Elsevier, vol. 98(C).
    16. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2022. "STARTUPS: Founding airlines during COVID-19 - A hopeless endeavor or an ample opportunity for a better aviation system?," Transport Policy, Elsevier, vol. 118(C), pages 10-19.
    17. Lasha Labadze & Mohamed M. Sraieb, 2023. "Impact of Anti-Pandemic Policy Stringency on Firms’ Profitability during COVID-19," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    18. Li, Tao & Rong, Lili, 2022. "Spatiotemporally complementary effect of high-speed rail network on robustness of aviation network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 95-114.
    19. Yu, Meng & Chen, Zhenhua, 2021. "The effect of aviation responses to the control of imported COVID-19 cases," Journal of Air Transport Management, Elsevier, vol. 97(C).
    20. Kuo, Pei-Fen & Brawiswa Putra, I Gede & Setiawan, Faizal Azmi & Wen, Tzai-Hung & Chiu, Chui-Sheng & Sulistyah, Umroh Dian, 2022. "The impact of the COVID-19 pandemic on O-D flow and airport networks in the origin country and in Northeast Asia," Journal of Air Transport Management, Elsevier, vol. 100(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15618-:d:983195. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.