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BFL-Guard: A Blockchain-Enabled Federated Learning Framework with Zero-Knowledge Gradient Verification and Tokenized Incentives

Author

Listed:
  • Kumaresan S

    (Assistant Professor Department of EEE PGP college of Engineering and Technology, Namakkal, Tamil Nadu, India)

  • Thirumal L

    (Assistant Professor Varuvan Vadivelan Institute of Technology)

  • Dr. S. Sathish Kumar

    (Assistant Professor, Department of Electronics and Communication Engineering (ECE), Mahendra Institute of Technology, Namakkal, Tamil Nadu, India)

  • Ellappan V

    (Assistant Professor Department of ECE Mahendra Institute of Technology, Namakkal, Tamil Nadu India)

  • Selvam R

    (Assistant Professor Department of ECE Mahendra Institute of Technology, Namakkal, Tamil Nadu India)

Abstract

Federated Learning (FL) enables collaborative model training across decentralized participants without sharing raw data. However, existing FL systems remain vulnerable to Byzantine attacks and suffer from a lack of accountability, verifiability, and economic incentives for honest participation. We present BFL-Guard, a novel blockchain-orchestrated federated learning framework integrating: (i) zk-SNARK-based zero-knowledge gradient proofs, (ii) an on-chain Byzantine-tolerant aggregation smart contract, and (iii) a tokenized incentive protocol (FedToken). BFL-Guard stores model checkpoints as IPFS hashes anchored on Ethereum, ensuring tamper-evident auditability. Experiments on CIFAR-10 and Shakespeare benchmarks demonstrate 95.2% and 87.6% accuracy in IID and Non-IID settings, surpassing all baselines while converging 12.4% faster even under 30% Byzantine injection.

Suggested Citation

  • Kumaresan S & Thirumal L & Dr. S. Sathish Kumar & Ellappan V & Selvam R, 2026. "BFL-Guard: A Blockchain-Enabled Federated Learning Framework with Zero-Knowledge Gradient Verification and Tokenized Incentives," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(6), pages 2541-2550, July.
    • Handle: RePEc:bjf:ijltem:v:15:y:2026:i:6:a:3007
    DOI: 10.51583/IJLTEMAS.2026.150600186
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