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A New Hybrid Online and Offline Multi-Factor Cross-Domain Authentication Method for IoT Applications in the Automotive Industry

Author

Listed:
  • Haqi Khalid

    (Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Shaiful Jahari Hashim

    (Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Sharifah Mumtazah Syed Ahmad

    (Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Fazirulhisyam Hashim

    (Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang 43400, Malaysia)

  • Muhammad Akmal Chaudhary

    (Department of Electrical and Computer Engineering, College of Engineering and Information Technology, Ajman University, Ajman 346, United Arab Emirates)

Abstract

Connected vehicles have emerged as the latest revolution in the automotive industry, utilizing the advent of the Internet of Things (IoT). However, most IoT-connected cars mechanisms currently depend on available network services and need continuous network connections to allow users to connect to their vehicles. Nevertheless, the connectivity availability shortcoming in remote or rural areas with no network coverage makes vehicle sharing or any IoT-connected device problematic and undesirable. Furthermore, IoT-connected cars are vulnerable to various passive and active attacks (e.g., replay attacks, MiTM attacks, impersonation attacks, and offline guessing attacks). Adversaries could all use these attacks to disrupt networks posing a threat to the entire automotive industry. Therefore, to overcome this issue, we propose a hybrid online and offline multi-factor authentication cross-domain authentication method for a connected car-sharing environment based on the user’s smartphone. The proposed scheme lets users book a vehicle using the online booking phase based on the secured and trusted Kerberos workflow. Furthermore, an offline authentication phase uses the OTP algorithm to authenticate registered users even if the connectivity services are unavailable. The proposed scheme uses the AES-ECC algorithm to provide secure communication and efficient key management. The formal SOV logic verification was used to demonstrate the security of the proposed scheme. Furthermore, the AVISPA tool has been used to check that the proposed scheme is secured against passive and active attacks. Compared to the previous works, the scheme requires less computation due to the lightweight cryptographic algorithms utilized. Finally, the results showed that the proposed system provides seamless, secure, and efficient authentication operation for the automotive industry, specifically car-sharing systems, making the proposed system suitable for applications in limited and intermittent network connections.

Suggested Citation

  • Haqi Khalid & Shaiful Jahari Hashim & Sharifah Mumtazah Syed Ahmad & Fazirulhisyam Hashim & Muhammad Akmal Chaudhary, 2021. "A New Hybrid Online and Offline Multi-Factor Cross-Domain Authentication Method for IoT Applications in the Automotive Industry," Energies, MDPI, vol. 14(21), pages 1-34, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7437-:d:674548
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    References listed on IDEAS

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    1. Fotios Zantalis & Grigorios Koulouras & Sotiris Karabetsos & Dionisis Kandris, 2019. "A Review of Machine Learning and IoT in Smart Transportation," Future Internet, MDPI, vol. 11(4), pages 1-23, April.
    2. Adnan Mahmood & Wei Emma Zhang & Quan Z. Sheng, 2019. "Software-Defined Heterogeneous Vehicular Networking: The Architectural Design and Open Challenges," Future Internet, MDPI, vol. 11(3), pages 1-17, March.
    3. Manar Abu Talib & Sohail Abbas & Qassim Nasir & Mohamad Fouzi Mowakeh, 2018. "Systematic literature review on Internet-of-Vehicles communication security," International Journal of Distributed Sensor Networks, , vol. 14(12), pages 15501477188, December.
    4. Fu, Xiuwen & Yang, Yongsheng, 2021. "Analysis on invulnerability of wireless sensor networks based on cellular automata," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
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    1. Kakkar, Riya & Agrawal, Smita & Tanwar, Sudeep, 2024. "A systematic survey on demand response management schemes for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 203(C).

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