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An Attribute-Based Access Control for IoT Using Blockchain and Smart Contracts

Author

Listed:
  • Syed Yawar Abbas Zaidi

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44500, Pakistan)

  • Munam Ali Shah

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44500, Pakistan)

  • Hasan Ali Khattak

    (School of Electrical Engineering and Computer Science, National University of Sciences and Technology (NUST), Islamabad 44500, Pakistan)

  • Carsten Maple

    (Secure Cyber Systems Research Group (SCSRG), University of Warwick, Coventry CV4 7AL, UK)

  • Hafiz Tayyab Rauf

    (Department of Computer Science, Faculty of Engineering & Informatics, University of Bradford, Bradford BD7 1DP, UK)

  • Ahmed M. El-Sherbeeny

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Mohammed A. El-Meligy

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

Abstract

With opportunities brought by the Internet of Things (IoT), it is quite a challenge to maintain concurrency and privacy when a huge number of resource-constrained distributed devices are involved. Blockchain have become popular for its benefits, including decentralization, persistence, immutability, auditability, and consensus. Great attention has been received by the IoT based on the construction of distributed file systems worldwide. A new generation of IoT-based distributed file systems has been proposed with the integration of Blockchain technology, such as the Swarm and Interplanetary File System. By using IoT, new technical challenges, such as Credibility, Harmonization, large-volume data, heterogeneity, and constrained resources are arising. To ensure data security in IoT, centralized access control technologies do not provide credibility. In this work, we propose an attribute-based access control model for the IoT. The access control lists are not required for each device by the system. It enhances access management in terms of effectiveness. Moreover, we use blockchain technology for recording the attribute, avoiding data tempering, and eliminating a single point of failure at edge computing devices. IoT devices control the user’s environment as well as his or her private data collection; therefore, the exposure of the user’s personal data to non-trusted private and public servers may result in privacy leakage. To automate the system, smart contracts are used for data accessing, whereas Proof of Authority is used for enhancing the system’s performance and optimizing gas consumption. Through smart contracts, ciphertext can be stored on a blockchain by the data owner. Data can only be decrypted in a valid access period, whereas in blockchains, the trace function is achieved by the storage of invocation and the creation of smart contracts. Scalability issues can also be resolved by using the multichain blockchain. Eventually, it is concluded from the simulation results that the proposed system is efficient for IoT.

Suggested Citation

  • Syed Yawar Abbas Zaidi & Munam Ali Shah & Hasan Ali Khattak & Carsten Maple & Hafiz Tayyab Rauf & Ahmed M. El-Sherbeeny & Mohammed A. El-Meligy, 2021. "An Attribute-Based Access Control for IoT Using Blockchain and Smart Contracts," Sustainability, MDPI, vol. 13(19), pages 1-26, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:10556-:d:641425
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    References listed on IDEAS

    as
    1. Lee, In & Lee, Kyoochun, 2015. "The Internet of Things (IoT): Applications, investments, and challenges for enterprises," Business Horizons, Elsevier, vol. 58(4), pages 431-440.
    2. Israr Ahmad & Munam Ali Shah & Hasan Ali Khattak & Zoobia Ameer & Murad Khan & Kijun Han, 2020. "FIViz: Forensics Investigation through Visualization for Malware in Internet of Things," Sustainability, MDPI, vol. 12(18), pages 1-23, September.
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    Cited by:

    1. Raed M. Bani-Hani & Ahmed S. Shatnawi & Lana Al-Yahya, 2024. "Vulnerability Detection and Classification of Ethereum Smart Contracts Using Deep Learning," Future Internet, MDPI, vol. 16(9), pages 1-35, September.
    2. Evin Özkan & Neda Azizi & Omid Haass, 2021. "Leveraging Smart Contract in Project Procurement through DLT to Gain Sustainable Competitive Advantages," Sustainability, MDPI, vol. 13(23), pages 1-25, December.

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