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Enhancing IIOT security using ML with Blockchain technology

  • Unique Paper ID: 175685
  • Volume: 11
  • Issue: 11
  • PageNo: 3465-3479
  • Abstract:
  • The Internet of Things (IoT) brings significant commercial, financial, and societal implications for the way we live. Contributing nodes in these networks of the IoT setting are resource-restricted, making them susceptible to web-oriented attacks. In this work, significant attempts were undertaken to solve issues related to privacy and security in IoT networks, mostly using classic cryptographic algorithms. Nevertheless, the distinctive features of nodes in the IoT make current approaches in the literature to be inadequate to cover all aspects of the security spectrum of networks of the IoT setting. In this work, a cutting-edge, secure, and privacy-preserving framework tailored for machine learning models within the Industrial Internet of Things (IIoT) ecosystem, is implemented. The proposed solution synergizes four integral components: Distributed Entity/Branch (DISTEN) for robust model encryption, Central Authority/Coordinating Server (CENTAUTH) for comprehensive key management, the Interplanetary File System (IPFS) for scalable and efficient model storage, and the Ethereum Blockchain (ETHBC) for the immutable recording of transactions and verification of hashcodes. This innovative framework focuses on encrypting ML models using AES symmetric keys generated by CENTAUTH. Finally, we present the validation of the performance prospects of our IIOT security paradigm using ML with Blockchain technology.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 11
  • PageNo: 3465-3479

Enhancing IIOT security using ML with Blockchain technology

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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