Blockchain-based data storage mechanism for industrial Internet of things

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Wang, J., Chen, W., Wang, L., Ren, Y. and Sherratt, R. S. orcid id iconORCID: https://orcid.org/0000-0001-7899-4445 (2020) Blockchain-based data storage mechanism for industrial Internet of things. Intelligent Automation and Soft Computing, 26 (5). pp. 1157-1172. ISSN 2326-005X doi: 10.32604/iasc.2020.012174

Abstract/Summary

With the development of the Industrial Internet of Things and the continuous expansion of application scenarios, many development bottlenecks have followed. Its data security issue has become an obstacle to its widespread application. It has attracted substantial attention from both academia and industry. Blockchain technology has the characteristics of decentralization, openness and transparency and non-tampering. It has natural advantages in solving the security of the Industrial Internet of Things. Accordingly, this paper first analyzes the security risks associated with data storage in the Industrial Internet of Things and proposes the use of blockchain technology to ensure the secure storage of data in the Industrial Internet of Things. In traditional blockchains, the data layer uses Merkle hash trees to store data; however, the Merkle hash tree not able to provide non-member proof, which makes it unable to resist attacks from malicious nodes in the network. To solve this problem, this paper replaces the Merkle hash tree with a password accumulator to provide member proof and non-member proof. Moreover, the existing accumulators have trapdoors and cannot be updated in batches, and unable to meet the blockchain’s expansion requirements. This paper presents an improved RSA accumulator and gives the definition of the accumulator. Finally, this paper uses RSA to construct a batch update accumulator scheme without trapdoor, and shows that the scheme is feasible through correctness and security

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/95533
Identification Number/DOI 10.32604/iasc.2020.012174
Refereed Yes
Divisions Life Sciences > School of Biological Sciences > Department of Bio-Engineering
Publisher Taylor & Francis
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