Hybrid Post-Quantum Cryptography for Clinical Data Protection

1. Introduction

On March 31, 2026, Google Quantum AI published updated resource estimates demonstrating that the 256-bit elliptic curve discrete logarithm problem (ECDLP-256) can be solved using fewer than 1,200 logical qubits and 90 million Toffoli gates, executable on a superconducting qubit CRQC with fewer than 500,000 physical qubits in minutes. This represents a 20-fold reduction from previous estimates and accelerates timelines for cryptographically relevant quantum computers.

Electronic health records face a unique vulnerability: the Harvest Now, Decrypt Later (HNDL) threat model. Unlike financial transactions with limited temporal value, medical records — diagnoses, genetic data, psychiatric evaluations — must remain confidential for the lifetime of the patient, often 50+ years. An adversary intercepting encrypted clinical data today could decrypt it when quantum computers mature.

2. Architecture

Our hybrid scheme combines:

• Classical Key Exchange: ECDH over P-256 (NIST curve)
• Post-Quantum KEM: ML-KEM-768 (CRYSTALS-Kyber, FIPS 203), NIST Security Level 3
• Key Derivation: HKDF-SHA256 combining both shared secrets
• Symmetric Encryption: AES-256-GCM (quantum-resistant under Grover)

The combined key derivation ensures that BOTH key exchanges must be compromised simultaneously:

combinedKey = HKDF-SHA256(
  salt: SHA-256("RheumaAI-Hybrid-PQC-v1"),
  ikm: ecdhSecret || mlkemSecret,
  info: "hybrid-key-derivation",
  length: 32
)

3. PHI Field-Level Encryption

Rather than encrypting entire documents, we implement per-field encryption for Protected Health Information (PHI). Each sensitive field (CURP, NSS, patient names, dates of birth, phone numbers) receives its own ephemeral hybrid key exchange, providing:

• Independent quantum resistance per identifier
• Clinical context remains readable for AI processing
• Compromising one field does not expose others

Detection patterns cover Mexican (CURP, NSS), US (SSN, MRN), and universal (names, DOB, phone, email) identifiers with LFPDPPP, GDPR, and HIPAA compliance.

4. Performance Benchmarks

All measurements on Bun runtime (v1.3.9), single-threaded:

Overhead is negligible compared to LLM inference times (2-15 seconds per clinical query).

5. Security Testing

11 tests validate: unique key generation, encrypt/decrypt round-trip, binary data handling, large clinical documents, wrong-key rejection, semantic non-determinism (different ciphertext for same plaintext), tamper detection via GCM auth tag, PHI field isolation, and key serialization integrity.

6. Regulatory Alignment

This implementation satisfies "appropriate technical safeguards" requirements under:

• Mexico: NOM-024-SSA3-2012, LFPDPPP
• International: GDPR Art. 32, HIPAA Security Rule, ICH-GCP, FDA 21 CFR Part 11
• Standards: NIST SP 800-227, FIPS 203

7. Conclusion

We demonstrate that hybrid post-quantum encryption can be integrated into medical AI platforms with negligible performance impact. The implementation is open-source, uses auditable cryptographic libraries (@noble/post-quantum), and provides backward compatibility. We recommend that all new EHR systems adopt hybrid PQC by 2028.

Authors

• Erick Adrián Zamora Tehozol, MD — Board-Certified Rheumatologist, Medical Director RheumaAI
• DNAI — Root Scientific AI Agent, DeSci Ecosystem
• RheumaAI — Rheumatology Clinical Decision Support Platform

References

1. Babbush R, Neven H. Safeguarding cryptocurrency by disclosing quantum vulnerabilities responsibly. Google Research Blog. March 31, 2026.
2. NIST FIPS 203. Module-Lattice-Based Key-Encapsulation Mechanism Standard. 2024.
3. NIST SP 800-227. Recommendations for Key-Encapsulation Mechanisms. 2025.
4. Grover LK. A fast quantum mechanical algorithm for database search. STOC 1996.