OsamahNNeamah/QDNA-ID

🧬 QDNA-ID — Quantum Device Native Authentication
Developed by: Osamah N. Neamah
Institution: Department of Mechatronic Engineering, Graduate Institute, Karabuk University, Karabuk, Turkey.

A quantum provenance dashboard that links physical device behavior
to cryptographically verifiable, signed fingerprints.
A complete trust chain connecting physical quantum behavior to digital verification. The code shown here is a simplified V0 example only and does not represent the exact workings. The dataset shown is the same data used for the Proof-of-Concept tests.

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Citation

If you use QDNA-ID in your research, please cite:

QDNA-ID: Quantum Device Native Authentication, http://arxiv.org/abs/2511.17692.

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🧠 Project Overview

QDNA-ID introduces a quantum provenance framework that couples quantum hardware behavior with
digitally verifiable cryptographic records. Each quantum execution generates a fingerprint that is:

1. Measured on a real IBM Quantum device.
2. Characterized by quantum-mechanical metrics (e.g., CHSH S-value).
3. Encoded into a deterministic feature vector.
4. Digitally signed & timestamped using HMAC-SHA256 and RSA-PSS-SHA256.
5. Stored and verifiable as a reproducible provenance record.

This provides a measurable and cryptographically sealed identity for each quantum device run —
bridging physical quantum entropy with digital cryptographic trust.

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🧩 Key Features

• ✅ Hardware-based measurement (no simulators; tested on real IBM Quantum devices).
• 🔐 Dual cryptographic signatures — HMAC-SHA256 (symmetric) & RSA-PSS-SHA256 (asymmetric).
• 📈 CHSH-S Quantum Verification — non-classical correlation score (≥ 2.0 required).
• 🧾 Provenance Metadata — full environment capture: runtime versions, device ID, timestamps.
• 🧮 Feature Extraction — converts raw counts to structured quantum fingerprints.
• 🗃️ Hierarchical Storage —
  qdna_sessions// ├── _raw.json ├── _features.json └── _sign.json

ruby Copy code

• 🌐 Streamlit Dashboard — live display of CHSH metrics, signatures, and device provenance.

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🧪 Technical Stack

Layer	Technology	Purpose
Quantum Execution	Qiskit	Circuit transpilation and IBM backend interface
Runtime	qiskit_ibm_runtime.SamplerV2	Hardware job submission
Cryptography	cryptography.hazmat	HMAC & RSA (SHA-256)
Visualization	Streamlit	Interactive provenance dashboard
Storage	JSON + filesystem	Immutable provenance store
Environment	Python ≥ 3.10	Recommended for full reproducibility

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⚙️ Installation

# Clone repository
git clone https://github.com/osamah-nn/qDNA-ID.git
cd qDNA-ID

# (Optional) create environment
python -m venv qdnaidex
source qdnaidex/bin/activate   # or .\qdnaidex\Scripts\activate on Windows

# Install dependencies
pip install -r qdna_id.yml
Dependencies:
qiskit, qiskit-ibm-runtime, cryptography, numpy, streamlit, pandas


🔑 Environment Configuration
Before running, set cryptographic and IBM environment variables:
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IBM (Configure devices.py by your IBM Cloud ConfigurationS)
# === Your static configuration (with ENV overrides allowed) === 
# Windows
setx QISKIT_IBM_RUNTIME_API_TOKEN "Your API IBM TOKEN"
# Linux 
export QISKIT_IBM_RUNTIME_API_TOKEN="Your API IBM TOKEN"
🚀 Running a Quantum Session
Run directly from command line:

bash
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python challenge.py --backend ibm_torino --shots 1024
Output Example

ini
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CHSH_S=2.39
RAW_FILE=qdna_sessions/ibm_kyiv/QDNAID20251017163045_raw.json
FEATURES_FILE=qdna_sessions/ibm_kyiv/QDNAID20251017163045_features.json
SIGN_FILE=qdna_sessions/ibm_kyiv/QDNAID20251017163045_sign.json
Or start the dashboard:

bash
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streamlit run app.py
📊 Output Files
File	Description
*_raw.json	Original quantum counts + full provenance metadata
*_features.json	Extracted metrics including chsh_S
*_sign.json	Digital signatures (HMAC + RSA) + pubkey fingerprint

🔬 Quantum Provenance Workflow
java
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Quantum Hardware → Counts → CHSH Verification
       ↓
 Feature Vectorization
       ↓
 Cryptographic Signing (HMAC + RSA)
       ↓
 Provenance Store (Immutable JSON)
       ↓
 Streamlit Dashboard / Verification API
Each record forms a verifiable “QDNA-ID” chain, connecting physical behavior
to digital authentication — enabling reproducibility, security, and trust.

🧾 Example Signatures Block
json
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"signatures": {
  "hmac_sha256": "b4e9b1f...c74",
  "rsa_sha256_hex": "9d3b...1f",
  "algorithms": {
    "hmac": "HMAC-SHA256",
    "rsa": "RSA-PSS-SHA256"
  },
  "key_ids": {
    "hmac": "dev-hmac-01",
    "rsa": "dev-rsa-01"
  },
  "pubkey_fingerprint_sha256": "e3c0...9fa",
  "created_at_utc": "2025-10-17T15:23:12Z"
}
🧮 Academic Context
Discipline: Quantum Computing, Cryptography, Provenance Informatics

Institution: Karabuk University

Research Group: Quantum Provenance Initiative


Lead Developer: Osamah N. Neamah

This project serves as an academic Proof-of-Concept (PoC) — demonstrating a full-chain
quantum trust model from hardware to digital signature.

⚠️ License & Notice
© 2025 QDNA-ID — Academic PoC License

This work is provided for academic and research use only.
Unauthorized commercial use, redistribution, or derivative production is prohibited
without explicit written consent from the author.

📬 Contact
Author: Osamah N. Neamah

Institution: Karabuk University — Quantum Provenance Initiative

Email: [email protected]

LinkedIn: linkedin.com/in/osamah-n-neamah-b2774118b

Website: qdnaid.org (coming soon)