Journal of Machine and Computing


Trusted Mechanism for Malware Detection Using Blockchain with Minimal Overhead of Data Integrity for IIoT



Journal of Machine and Computing

Received On : 30 August 2024

Revised On : 26 October 2024

Accepted On : 26 November 2024

Volume 05, Issue 01


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Abstract


A trusted mechanism for detecting malware in Industrial Internet of Things (IIoT) using blockchain technology is proposed. The proposed mechanism leverages the immutability and decentralization features of blockchain to ensure the integrity of the malware detection process, while minimizing the overhead associated with data integrity. The mechanism involves the use of a consensus algorithm, Proof of Authority (PoA) to validate malware detection results and a smart contract to enforce the consensus rules. Experimental results show that the proposed approach can efficiently detect malware in IIoT environments with minimal impact on system performance. The proposed architecture is thoroughly validated using MATLAB and a variety of security criteria, including attack strength, message alteration, and false validation probability. Based on the obtained results, the suggested method is effective in improving the security of IIoT networks by detecting malware attacks within the network. The proposed mechanism provides a promising solution for enhancing the security of IIoT systems, which are becoming increasingly vulnerable to cyber-attacks.


Keywords


Industrial Internet of Things (IIoT), Data Integrity, Malware Detection, Minimal Overhead, Security.


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We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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Cite this article


Swathiramya R, Padmashri N, Sathish Kumar Ravichandran and Lekhaa T R, “Trusted Mechanism for Malware Detection Using Blockchain with Minimal Overhead of Data Integrity for IIoT”, Journal of Machine and Computing. doi: 10.53759/7669/jmc202505030.


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© 2025 Swathiramya R, Padmashri N, Sathish Kumar Ravichandran and Lekhaa T R. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.