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All Journal International Journal of Computer Technology and Science
Mohammad Hamka Izzuddin Bin Mohamad Yahya
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Computer Science & IT

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Enhancing IIoT Security: AI-Driven Blockchain-Based Authentication Scheme Azreen Shafieqah Asri; Faizatul Fitri Boestamam; Harith Zakwan Bin Zakaria; Mohammad Amir Alam Rahim Omar; Mohammad Hamka Izzuddin Bin Mohamad Yahya; Muhammad Faisal
International Journal of Computer Technology and Science Vol. 1 No. 3 (2024): July : International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i3.19

Abstract

With the rapid expansion of the Industrial Internet of Things (IIoT), integrating devices, machines, and systems to optimize operations and enable data-driven decision-making, ensuring robust security measures is essential. While blockchain has shown the potential to upgrade traditional authentication methods in IIoT environments, vulnerabilities persist. This paper introduces two innovative methods to enhance blockchain-based authentication in IIoT: first, integrating AI-driven anomaly and threat detection into the blockchain authentication scheme; second, implementing Ethereum smart contracts for enhanced authentication with a two-factor authentication (2FA) system and GFE algorithms. By combining AI for anomaly detection with decentralized smart contracts and blockchain-based 2FA, and leveraging GFE algorithms to enhance blockchain capabilities, the proposed scheme aims to significantly fortify security measures. This integration offers a resilient defense against evolving threats, ensuring transparency, adaptability, and heightened security in IIoT applications.
Co-Authors Azreen Shafieqah Asri Faizatul Fitri Boestamam Harith Zakwan Bin Zakaria Mohammad Amir Alam Rahim Omar Muhammad Faisal