An Adaptive Quantum-Resilient Self-Sovereign Identity (AQR-SSI) Framework Using Blockchain, Zero-Knowledge Proofs, and Explainable AI for Secure Electronic Health Records Sharing

The digitization of Electronic Health Records (EHRs) has significantly improved care coordination, but has concurrently aggregated highly sensitive identity and clinical access data into centralized repositories. These repositories serve as attractive targets for unauthorized breach, insider misuse, and, with the rapid development of cryptographically relevant quantum computers, future retrospective decryption (commonly known as “harvest-now, decrypt-later” attacks). This paper presents AQR-SSI, an Adaptive Quantum-Resilient Self-Sovereign Identity framework designed to address these fundamental vulnerabilities. The architecture seamlessly integrates: (i) a permissioned blockchain ledger for decentralized identifiers (DIDs) and verifiable credentials (VCs); (ii) zero-knowledge proofs (ZKPs) for unlinkable, selective disclosure of patient attributes during Electronic Health Record (EHR) sharing; (iii) a hybrid post-quantum cryptographic (PQC) suite combining NIST-standardized lattice- and hash-based primitives (ML-DSA, Falcon, SPHINCS+, ML-KEM) with classical algorithms to facilitate a secure migration period; and (iv) an explainable AI (XAI) monitoring layer that continuously audits access requests and generates human-readable explanations for anomaly flags via SHAP and LIME-based attributions. We detailed the structural reference architecture. We also described the actor and trust model, cryptographic protocol design, smart-contract-based consent and revocation mechanisms, and conducted an in-depth, threat-model-driven security analysis. Additionally, we provide an illustrative, literature-grounded performance analysis estimating the computational and storage overhead of the hybrid signature scheme relative to classical elliptic-curve baselines, and discuss strict compliance alignment under HIPAA and GDPR. The AQR-SSI framework is structurally adaptive: its built-in cryptographic agility ensures algorithm suites can be easily swapped as NIST standards evolve, while the XAI layer remains fully auditable as the underlying anomaly detection models undergo periodic retraining. We conclude by identifying key open problems to prioritize in empirical follow-up work, specifically focusing on on-chain ZKP verification cost at scale, PQC signature bloat, and the real-world usability of patient-held digital wallets.

Keywords: Self-sovereign identity, Blockchain, Zero-knowledge proofs, Explainable AI, Electronic health records.