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Multi-Blockchain-Based IoT Data Processing Techniques to Ensure the Integrity of IoT Data in AIoT Edge Computing

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  • 1College of General Education, Semyung University, Jechon-si 27136, Korea.

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Summary

This study introduces a blockchain-based technique for verifying the integrity of Internet of Things (IoT) big data. It ensures data safety for auditors and minimizes information loss in AIoT systems.

Keywords:
AIoT edge computingcross-distributed and blockchain linkage processingintegrity of IoT datamultiple blockchainsynchronization using location information

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Area of Science:

  • Computer Science
  • Information Technology
  • Cybersecurity

Background:

  • Rapid advancements in Internet of Things (IoT) technologies generate vast amounts of data.
  • Current IoT data processing primarily focuses on monitoring and control, facing challenges with increasing data collection and linkage costs.
  • The need for proactive integration and smart analysis of IoT data by cloud servers is critical.

Purpose of the Study:

  • To propose a novel blockchain-based technique for verifying the integrity of IoT big data.
  • To enhance the security and trustworthiness of Third Party Auditors (TPAs) involved in Artificial Intelligence of Things (AIoT) data auditing.
  • To minimize IoT information loss and ensure data integrity within AIoT ecosystems.

Main Methods:

  • Implementing a blockchain-based framework for IoT big data integrity verification.
  • Utilizing multiple blockchain groupings for information and signature keys from IoT devices to minimize data loss.
  • Employing hierarchical chains that link hash values of constant-size blocks to ensure data integrity.
  • Leveraging location information for synchronization between central servers and IoT devices to manage integrity costs.
  • Applying cross-distributed and blockchain linkage processing under defined rules to manage numerous IoT device locations and improve system load and throughput.

Main Results:

  • The proposed technique effectively guarantees the integrity of AIoT data through a secure, blockchain-linked structure.
  • Minimization of IoT information loss is achieved via multi-blockchain grouping of data and keys.
  • Efficient management of integrity costs is realized through location-based synchronization and optimized processing.
  • Improved load and throughput for systems managing a large number of IoT devices.

Conclusions:

  • The developed blockchain-based technique provides a robust solution for ensuring the integrity and security of IoT big data.
  • This approach addresses the challenges of cost and data loss in AIoT data processing and auditing.
  • The method enhances the overall efficiency and reliability of AIoT systems through distributed ledger technology and optimized data management.