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CITADEL: a post-quantum secure blockchain framework for privacy-preserving electronic health records with
Nagaraj Segar1, Vijayarajan Vijayan1
1School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology (VIT), Vellore, India.
Introduction:
Electronic health records (EHRs) increasingly anchor clinical decision support and population-scale analytics, yet their concentration of sensitive information amplifies disclosure risk, widens the attack surface, and faces emerging threats from quantum computing. Existing frameworks fail to simultaneously address privacy preservation, quantum-resistant security, and cross-institutional federated learning.
Methods:
We introduce CITADEL (Cryptographically Integrated Temporal Architecture for Distributed EHR Ledger), integrating five co-designed components: NIST-standardized CRYSTALS-Kyber (ML-KEM-768) and CRYSTALS-Dilithium (ML-DSA-65) post-quantum cryptography via the validated pqcrypto library; a genomic-aware privacy engine with beacon query protection and calibrated randomized response; temporally-partitioned federated learning with hospital-specific weighted aggregation; multi-modal health data tokenization; and an adaptive regulatory compliance engine for HIPAA and GDPR. Evaluation used a synthetic EHR dataset comprising 5,000 patients across 10 healthcare institutions, with 30-day hospital readmission as the primary prediction task.
Results:
CITADEL achieves 84.5% accuracy and 0.866 AUC-ROC, exceeding nine baselines including centralized neural networks and differentially-private federated learning. Privacy metrics include k-anonymity of 13, l-diversity of 2.0, 99.0% linkage attack resistance, 42.2% attribute inference resistance, and 100% correlation preservation. The ledger sustains 285.3 transactions per second with ML-DSA-65 signing in 2.16 ms and verification in 0.46 ms. Multi-seed evaluation confirms robustness (accuracy 0.854 ± 0.012, AUC-ROC 0.880 ± 0.014).
Discussion:
CITADEL demonstrates that privacy preservation, quantum-resistant security, and usable federated analytics can be reconciled within one cohesive architecture. Results suggest a practical route to healthcare data management that remains credible in a post-quantum computing era and compatible with decentralized governance.
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