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A security framework to enhance IoT device identity and data access through blockchain consensus model

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Abstract

In today’s technology landscape, the Internet of Things (IoT) has gained significant momentum due to its wide-ranging applications across diverse devices. However, the integration of IoT faces several daunting challenges, with security emerging as a paramount concern. To address this, blockchain technology has emerged as a decentralized and foundational solution for mitigating these integration obstacles. This research introduces a reliable blockchain-based consensus PIoT (Proof of Internet of Things) specifically for IoT networks, aiming to overcome the attacks encountered during data communication. The proposed blockchain system excels in effectively identifying IoT devices, authenticating their legitimacy, and dynamically assigning addresses based on demand. Additionally, it offers secure communication capabilities among IoT devices, providing robust protection against various attacks. The performance of PIoT is superior than that of certain traditional techniques. As it comes to the efficient use of available time, PIoT displays improvements of 74.7 and 96.8%, respectively, as compared to LPBFT and hybrid blockchain. In addition to this, the level of consensus security offered by PIoT is 15% higher than that offered by DAC4SH. PIoT has impressive scalability in terms of time consumption, the fraction of successful consensus attempts, and transaction throughput even when the network size and the number of malicious nodes face exponential variations.

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Authors and Affiliations

  1. Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu, India

    Janani Kariyappa & Ramamoorthy Sriramulu

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  1. Janani Kariyappa
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  2. Ramamoorthy Sriramulu
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Author A and B both are having a equal contribution

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Correspondence to Ramamoorthy Sriramulu.

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Janani, K., Ramamoorthy, S. A security framework to enhance IoT device identity and data access through blockchain consensus model. Cluster Comput 27, 2877–2900 (2024). https://doi.org/10.1007/s10586-023-04113-8

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