Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{204456,
        author = {Roopa S Kumar},
        title = {Blockchain With AI Support: A Consensus Protocol That Recognizes Outliers for IoT Networks Based on Blockchain},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {123-128},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=204456},
        abstract = {A new framework using machine learning for secure consensus in IoT networks based on blockchain. Despite its suitability for IoT applications, Hyperledger Fabric struggles with malicious activities in untrustworthy environments. The solution is an AI-enabled blockchain (AIBC) that uses an outlier detection algorithm within a two-step consensus protocol. In the first stage, a supervised machine learning method is used to identify anomalous activity. The Practical Byzantine Fault Tolerance (PBFT) protocol is then used for ledger updates. The performance results show that the AIBC network improves the fault tolerance of Hyperledger Fabric, with only a slight impact on the delay performance.},
        keywords = {.},
        month = {June},
        }