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

Mahmood A Al-Shareeda1, Selvakumar Manickam1

  • 1National Advanced IPv6 Centre (NAv6), Universiti Sains Malaysia, George Town 11800, Penang, Malaysia.

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This study introduces a novel COVID-19 vehicle detection system using 5G vehicular fog computing. The efficient mutual authentication scheme enhances road safety and healthcare monitoring during pandemics.

Keywords:
5G-enabled vehicular networkCOVID-19 vehicleauthenticationfog server

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Area of Science:

  • Computer Science
  • Public Health
  • Network Security

Background:

  • The COVID-19 pandemic has severely impacted global society, with transportation systems identified as key transmission routes.
  • Current infection tracking and healthcare monitoring in high-mobility transport are impractical for effective pandemic control.
  • 5G-enabled vehicular fog computing offers potential for non-contact autonomous healthcare monitoring to improve road safety.

Purpose of the Study:

  • To propose an efficient mutual authentication scheme for 5G-enabled vehicular fog computing to address the automotive pandemic.
  • To develop a COVID-19 vehicle detection system for enhanced public health and road safety.
  • To ensure privacy and security requirements are met while providing effective COVID-19 and healthcare solutions.

Main Methods:

  • Development of a mutual authentication scheme utilizing a special flag (SF=0 for normal, SF=1 for COVID-19 vehicles).
  • Integration of 5G vehicular fog computing for data interpretation and autonomous healthcare monitoring.
  • Performance evaluation comparing communication and computation costs with existing related works.

Main Results:

  • The proposed scheme effectively distinguishes between normal and COVID-19 vehicles using the special flag.
  • The system satisfies essential privacy and security requirements for vehicular networks.
  • Performance evaluations demonstrate superior efficiency in communication and computation costs.

Conclusions:

  • The proposed COVID-19 vehicle detection scheme is efficient and secure for 5G-enabled vehicular fog computing.
  • This approach offers a viable solution for pandemic control within transportation systems.
  • The system enhances both road safety and autonomous healthcare monitoring capabilities.