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Using Hyperledger Fabric Blockchain to Improve Information Assurance of IoT Devices for AI Model Development

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Advances in Blockchain Technology for Cyber Physical Systems

Part of the book series: Internet of Things ((ITTCC))

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Abstract

This chapter aims to show that our research using the Hyperledger Fabric blockchain for Navy logistics assets can be applied to data supporting artificial intelligence (AI) and software development in terms of system safety and timely data acquisition. Data-driven AI/machine learning (ML) requires trusted data for their use in AI functions and requires significant amounts of training data from diverse sources including Internet of things (IoT) devices/sensors. Unauthorized alterations to data supporting AI/ML could go unnoticed within the AI function build process but surface during operation in hazards affecting unwanted human death or resource destruction. AI/ML controlling hardware usually falls into the two highest software control categories: Levels 1 and 2, risk of death, disability, or resource destroyed. We show how trust can be implemented through distributed consensus to ensure that only authorized people can modify data and that the modification is traceable and transparent. Distributed ledgers provide system safety through BC provenance, immutability, and policy enforcement through smart contracts. We also explain how Hyperledger Fabric could be used to provide data to researchers in a timely manner through “smart repositories” while ensuring provenance and integrity.

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Notes

  1. 1.

    The team was given access to the Oracle Cloud Platform thanks to the NPS liaison relationship with the Oracle Blockchain team.

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Author information

Authors and Affiliations

  1. Naval Postgraduate School, Monterey, CA, USA

    Anthony Kendall, Arijit Das, Bruce Nagy & Bonnie Johnson

  2. University of California, Berkeley, Berkeley, CA, USA

    Avantika Ghosh

Authors
  1. Anthony Kendall
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  2. Arijit Das
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  3. Bruce Nagy
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  4. Bonnie Johnson
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  5. Avantika Ghosh
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Corresponding author

Correspondence to Anthony Kendall .

Editor information

Editors and Affiliations

  1. ENSA Khouribga, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Yassine Maleh

  2. Computing and Cyber Security, Texas A&M University, San Antonio, TX, USA

    Lo’ai Tawalbeh

  3. ENSA, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Saad Motahhir

  4. Department of Computer Science, University of Montreal, Montreal, Quebec, QC, Canada

    Abdelhakim Senhaji Hafid

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Kendall, A., Das, A., Nagy, B., Johnson, B., Ghosh, A. (2022). Using Hyperledger Fabric Blockchain to Improve Information Assurance of IoT Devices for AI Model Development. In: Maleh, Y., Tawalbeh, L., Motahhir, S., Hafid, A.S. (eds) Advances in Blockchain Technology for Cyber Physical Systems. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-030-93646-4_11

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  • DOI: https://doi.org/10.1007/978-3-030-93646-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93645-7

  • Online ISBN: 978-3-030-93646-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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