abhi211b/qrfl repository overview

⁠QRFL — Threat-Timeline-Driven Quantum-Resistant Federated Learning for Blockchain-Enabled Healthcare Systems

QRFL is a reproducible research pipeline that integrates:

• Quantum-threat forecasting — models when large-scale quantum computers threaten current cryptography (Mosca/MOSCoW migration planning)
• NIST PQC benchmarking — ECDSA vs ML-DSA (Dilithium) / ML-KEM (Kyber) latency, key-size, and signature-size comparisons (quantcrypt-cffi backend)
• Healthcare federated learning — Classical / Hybrid / Native-PQ security modes benchmarked across 10 seeds × 50 rounds × 270 configs
• Hyperledger Fabric validation — ledger latency and throughput under each cryptographic mode
• Migration roadmap generation — architectural guidance for moving healthcare FL systems to post-quantum security

This image packages the full reproducibility pipeline used in the accompanying paper, so results can be regenerated deterministically from a single container.

⁠Quick start

docker pull abhi211b/qrfl:latest
docker run --rm -v $(pwd)/results:/app/results abhi211b/qrfl:latest

⁠Tags

⁠What's inside

• Forecasting, PQC benchmarking, FL experiment, resource profiling, statistical testing, and figure-generation modules
• Deterministic seeds; results/* and figures/output/* are regenerated on each run

⁠Reproducibility note for citation

For paper citations, pin the exact image digest rather than a mutable tag:

docker pull abhi211b/qrfl@sha256:14d043382ea73538c6893f42329daa87079fbd14948b61f888556cb02dcb5253

Get the digest with:

docker inspect --format='{{index .RepoDigests 0}}' abhi211b/qrfl:latest

...after pulling, or copy it from the "Tags" tab on Docker Hub.

⁠Source & documentation

• Source: https://github.com/abhishekeb211/qrfl-artifacts.git⁠
• Paper: <link once published / DOI when available>

⁠License

MIT

⁠Maintainer

CONTACT — Mr. Abhishek Raut, Mr. Saurabh V. Magdum