Blockchain Assisted Secure Data Sharing Model for Internet of Things Based Smart Industries

Gunasekaran Manogaran, Mamoun Alazab, P. Mohamed Shakeel, Ching Hsien Hsu

    Research output: Contribution to journalArticlepeer-review


    Industrial Internet of Things is focused to improve the performance of smart factories through automation and scalable functions. IoT paradigm, information and communication technology, and intelligent computing are assimilated as a single entity for industrial automation, optimization, sharing and security, and scalability. In a view of the security requirement in smart industry data sharing through IoT, this article introduces a blockchain-assisted secure data sharing (BSDS) model. This model is responsible for administering inbound and outbound security in data acquisition and dissemination. The inbound acquisition is first classified using recurrent learning to identify adverse sequences in data dissemination. In the outbound security measure, end-to-end authentication based on the blockchain information of reputation and sequence differentiation is engaged. The blockchain paradigm controls the data gathering and dissemination instances through the classification and integrity verification in both the industry and processing terminals. For this purpose, the functions of the blockchain are riven for data gathering and monitoring in the smart industry whereas integrity and sequence verification is performed by the nonmining blockchain terminal in the processing environment. The integrated security measures are capable of maximizing the response rate by confining false alarm progression, failure rate, and time delay. Statistical analysis shows that the BSDS achieves a 5.67% high response rate and reduces the failure rate by 2.14%. Further, it achieves 3.12% maximizes response rate by 6.63%, and reduces delay by 11.91% respectively.

    Original languageEnglish
    Pages (from-to) 348-358
    Number of pages11
    JournalIEEE Transactions on Reliability
    Issue number1
    Early online dateFeb 2021
    Publication statusPublished - 1 Mar 2022


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