INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026  
A Comprehensive Survey on Blockchain-Based Secure Storage  
Schemes for Medical Information  
1 Prashanth H S, 2 Dr. Srinidhi G A  
1 Department of Computer Science and Engineering, K.S Institute of Technology, Visveswaraya  
Technology, Bengaluru, Karnataka, India  
2 Department of Computer Science and Engineering (Cyber Security), Sri Siddhartha Institute of  
Technology Visveswaraya Technology, Tumkuru, Karnataka, India  
DOI : https://doi.org/10.51583/IJLTEMAS.2026.150100035  
Received: 14 January 2026; Accepted: 19 January 2026; Published: 28 January 2026  
ABSTRACT  
The exponential growth of digital healthcare data and the increasing need for secure, interoperable medical  
information systems have positioned blockchain technology as a promising solution for medical data storage  
and sharing. This survey provides a comprehensive analysis of blockchain-based secure storage schemes for  
medical information, examining 140+ research papers published between 2018-2025. We systematically  
categorize existing approaches into five primary themes: privacy-preserving storage mechanisms, access control  
frameworks, interoperability solutions, consensus and trust models, and smart contract implementations. Our  
analysis reveals that hybrid architectures combining on-chain metadata with off-chain encrypted storage  
(particularly using IPFS and cloud services) have emerged as the dominant paradigm. Key cryptographic  
techniques include attribute-based encryption (ABE), homomorphic encryption, and differential privacy for  
protecting sensitive medical data. We identify permissioned blockchain platforms, especially Hyperledger Fabric  
and Ethereum-based private networks, as preferred choices for healthcare consortiums. Major challenges include  
scalability limitations, regulatory compliance (HIPAA, GDPR), interoperability with legacy systems, and  
governance frameworks. Recent advancements focus on post-quantum cryptography integration, AI-enabled  
healthcare blockchains, and patient-centric digital twin implementations. This survey concludes with a  
discussion of future research directions, including quantum-resistant security schemes, cross-chain  
interoperability, and standardization efforts for blockchain-based healthcare systems.  
Keywords: Blockchain, Medical Information Security, Electronic Health Records, Healthcare Privacy, Secure  
Storage, Cryptographic Access Control  
INTRODUCTION  
Background and Motivation  
The healthcare industry generates an estimated 2.3 exabytes of data annually, with electronic health records  
(EHRs) becoming the cornerstone of modern medical practice [Zhang et al., 2021]. However, traditional  
centralized storage systems face significant challenges including data breaches, single points of failure, lack of  
patient control, and limited interoperability between healthcare providers. The 2023 Healthcare Data Breach  
Report indicates that over 133 million patient records were compromised, highlighting the urgent need for more  
secure storage solutions [Healthcare Security Report, 2024].  
Blockchain technology, originally conceptualized for cryptocurrency applications, has emerged as a  
transformative solution for healthcare data management due to its inherent properties of immutability,  
decentralization, transparency, and cryptographic security [Liu et al., 2018]. The distributed ledger technology  
offers unprecedented opportunities to address long-standing challenges in medical information systems while  
empowering patients with greater control over their health data.  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026  
Historical Context and Evolution  
The intersection of blockchain and healthcare began gaining academic attention around 2016, with early  
proposals focusing on simple data storage applications. The field has evolved through several distinct phases:  
Phase 1 (2016-2018): Conceptual Foundations - Basic blockchain applications for medical records - Simple  
hash-based integrity verification systems - Proof-of-concept implementations on public blockchains  
Phase 2 (2018-2020): Privacy-Aware Solutions - Integration of advanced cryptographic techniques -  
Development of hybrid on-chain/off-chain architectures - Introduction of smart contracts for access control  
Phase 3 (2020-2022): Production-Ready Systems - Permissioned blockchain adoption - Compliance with  
healthcare regulations (HIPAA, GDPR) - Large-scale pilot implementations  
Phase 4 (2022-Present): Advanced Integration - AI-blockchain convergence for healthcare - Post-quantum  
cryptographic schemes - Cross-chain interoperability solutions  
Current Trends and Challenges  
Contemporary blockchain-based medical storage systems face several critical challenges:  
1.  
Scalability Constraints: Traditional blockchain architectures struggle with the volume and velocity of  
healthcare data  
2.  
3.  
4.  
5.  
6.  
Privacy Paradox: Balancing transparency benefits with patient privacy requirements  
Regulatory Compliance: Navigating complex healthcare regulations across jurisdictions  
Integration Complexity: Interfacing with legacy healthcare information systems  
Energy Efficiency: Addressing environmental concerns of consensus mechanisms  
Standardization Gap: Lack of unified standards for blockchain healthcare implementations  
Survey Objectives and Contributions  
This comprehensive survey aims to:  
1.  
2.  
3.  
4.  
5.  
6.  
Systematically categorize existing blockchain-based secure storage schemes for medical information  
Analyze and compare different technical approaches, architectures, and cryptographic techniques  
Evaluate the strengths, limitations, and experimental findings of major frameworks  
Identify critical challenges and open research questions  
Discuss recent advancements and emerging trends  
Propose future research directions and opportunities  
LITERATURE REVIEW METHODOLOGY  
Search Strategy  
Our systematic literature review follows established guidelines for survey research in computer science. We  
conducted comprehensive searches across multiple academic databases including:  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026  
IEEE Xplore Digital Library  
ACM Digital Library  
PubMed/MEDLINE  
ScienceDirect  
SpringerLink  
Google Scholar  
arXiv preprint server  
Search Terms and Criteria  
Primary search terms included: - “blockchain medical data storage” - “secure healthcare blockchain” -  
“electronic health records blockchain” - “medical information privacy blockchain” - “healthcare data security  
distributed ledger”  
Inclusion Criteria: - Papers published between 2018-2025 - Focus on blockchain technology for  
medical/healthcare data - Security and privacy considerations - Peer-reviewed publications and high-quality  
preprints  
Exclusion Criteria: - Non-English publications - Purely theoretical papers without technical contributions -  
Duplicate studies or extended abstracts - Papers focused solely on cryptocurrency applications  
Data Extraction and Analysis  
We extracted the following information from each selected paper: - Technical approach and architecture -  
Blockchain platform used - Cryptographic techniques employed - Evaluation methodology and results -  
Identified limitations and challenges - Future work recommendations  
Taxonomy and Classification Framework  
Primary Classification Dimensions  
Based on our comprehensive analysis, we propose a multi-dimensional taxonomy for blockchain-based secure  
storage schemes for medical information:  
Architecture Dimension  
Pure On-Chain Storage: All medical data stored directly on blockchain  
Hybrid On-Chain/Off-Chain: Metadata on-chain, encrypted data off-chain  
Sidechain-Based: Dedicated medical data chains linked to main blockchain  
Cross-Chain: Multi-blockchain interoperability solutions  
Privacy Dimension  
Cryptographic Privacy: Using encryption, zero-knowledge proofs, etc.  
Anonymization Techniques: K-anonymity, differential privacy  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026  
Access Control Mechanisms: Attribute-based, role-based, policy-based  
Consent Management: Patient-controlled access permissions  
Blockchain Type Dimension  
Public Blockchains: Ethereum, Bitcoin-based solutions  
Private Blockchains: Enterprise-controlled networks  
Consortium Blockchains: Healthcare provider collaboratives  
Hybrid Blockchains: Combination of public and private elements  
Application Domain Dimension  
Electronic Health Records (EHR): Complete patient medical histories  
Medical Imaging: Radiology, pathology, and diagnostic images  
Genomic Data: DNA sequencing and genetic information  
IoT Healthcare Data: Wearable devices and sensor data  
Pharmaceutical Supply Chain: Drug traceability and authenticity  
Technical Architecture Patterns  
Our analysis reveals five dominant architectural patterns:  
Metadata-Centric Architecture  
This pattern stores only metadata, access permissions, and cryptographic hashes on the blockchain while keeping  
actual medical data in encrypted off-chain storage systems.  
Advantages: - Reduced blockchain storage requirements - Better scalability for large medical files - Compliance  
with data protection regulations  
Representative Systems: HealthChain [Chenthara et al., 2020], ACTION-EHR [Dubovitskaya et al., 2020]  
Smart Contract-Mediated Architecture  
Utilizes smart contracts to automate access control, consent management, and data sharing workflows.  
Key Features: - Programmable access policies - Automated compliance checking - Audit trail generation -  
Dynamic permission management  
Representative Systems: MedRec [Azaria et al., 2016], PatientChain [Zhang & Schmidt, 2017]  
Interledger Architecture  
Employs multiple interconnected blockchains to handle different aspects of medical data management.  
Components: - Main chain for identity and access management - Data chains for specific medical domains -  
Bridge protocols for cross-chain communication  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026  
Federated Learning Integration  
Combines blockchain with federated learning for privacy-preserving medical AI model training.  
Benefits: - Decentralized model training - Data remains locally stored - Blockchain ensures model integrity  
Digital Twin Architecture  
Creates blockchain-secured digital representations of patients for personalized healthcare.  
Applications: - Personalized treatment planning - Drug interaction modeling - Predictive health analytics  
Comparative Analysis of Key Methods and Frameworks  
Privacy-Preserving Storage Schemes  
Attribute-Based Encryption (ABE) Approaches  
Attribute-Based Encryption has emerged as a dominant cryptographic technique for fine-grained access control  
in medical blockchain systems.  
Ciphertext-Policy ABE (CP-ABE) - Principle: Encrypts data according to access policies embedded in  
ciphertext - Implementation: Liu et al. [2018] proposed BPDS system using CP-ABE for EHR sharing -  
Strengths: Fine-grained access control, policy flexibility - Limitations: Computational overhead, key  
management complexity  
Key-Policy ABE (KP-ABE) - Principle: Access policies embedded in user private keys - Applications: Less  
common in medical systems due to reduced flexibility - Use Cases: Suitable for role-based medical access  
scenarios  
Performance Comparison:  
Scheme Encryption Time  
Decryption Time  
O(log n)  
Storage Overhead  
High  
Access Control Granularity  
Fine-grained  
CP-  
O(n)  
ABE  
KP-  
ABE  
O(log n)  
O(n)  
O(1)  
Medium  
Low  
Coarse-grained  
Traditio O(1)  
Binary (all-or-nothing)  
nal  
RSA  
Homomorphic Encryption Integration  
Homomorphic encryption enables computation on encrypted medical data without decryption.  
Fully Homomorphic Encryption (FHE) - Applications: Statistical analysis on encrypted health records -  
Challenges: Significant computational overhead - Recent Advances: Lattice-based schemes showing improved  
efficiency  
Partially Homomorphic Encryption (PHE) - Variants: Additive (Paillier), multiplicative homomorphism -  
Use Cases: Aggregate health statistics, privacy-preserving analytics - Performance: More practical than FHE  
for specific operations  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue I, January 2026  
Zero-Knowledge Proof Systems  
zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) - Applications:  
Proving medical data validity without revealing content - Implementation: Zcash-inspired medical record  
verification systems - Benefits: Minimal proof size, efficient verification - Drawbacks: Trusted setup  
requirement  
zk-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge) - Advantages: No trusted  
setup, post-quantum security - Applications: Large-scale medical data verification - Status: Emerging in  
healthcare blockchain research  
Access Control Mechanisms  
Smart Contract-Based Access Control  
Smart contracts provide programmable, transparent, and immutable access control mechanisms for medical data.  
Policy-Based Access Control (PBAC) - Implementation: XACML-inspired policy languages in smart  
contracts - Features: Context-aware access decisions, dynamic policy updates - Example: Yaqub et al. [2025]  
blockchain-enabled policy-based access control  
Attribute-Based Access Control (ABAC) - Characteristics: User attributes, resource attributes, environmental  
conditions - Integration: Combined with ABE for comprehensive protection - Scalability: Challenges with  
large attribute sets  
Role-Based Access Control (RBAC) - Traditional Model: Hierarchical roles (doctor, nurse, patient, admin) -  
Blockchain Adaptation: Smart contract role management - Limitations: Less flexible than attribute-based  
approaches  
Consent Management Systems  
Dynamic Consent Frameworks - Patient Control: Granular permission management - Revocation  
Mechanisms: Real-time access withdrawal - Audit Trails: Immutable consent history  
GDPR Compliance Mechanisms - Right to be Forgotten: Challenges with blockchain immutability -  
Solutions: Off-chain data deletion, on-chain pointer invalidation - Data Portability: Blockchain-based patient  
data export  
Blockchain Platform Comparison  
Public Blockchain Platforms  
Ethereum - Advantages: Rich smart contract ecosystem, developer tools - Medical Applications: Patient-  
centric access control systems - Challenges: Scalability limitations, transaction costs, privacy concerns -  
Solutions: Layer 2 scaling, private Ethereum networks  
Bitcoin-Based Solutions - Approaches: Colored coins, sidechains for medical data - Limitations: Limited  
smart contract functionality - Use Cases: Simple integrity verification, timestamping  
Permissioned Blockchain Platforms  
Hyperledger Fabric - Architecture: Modular, permissioned network design - Healthcare Adoption: Widely  
used in consortium blockchain implementations - Features: Channel-based privacy, pluggable consensus,  
chaincode - Examples: Wu et al. [2024] EHR sharing system  
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Hyperledger Sawtooth - Consensus: Pluggable consensus mechanisms - Privacy: Transaction families for  
different data types - Applications: Multi-party healthcare data sharing  
R3 Corda - Design: Privacy-focused, point-to-point transactions - Healthcare Fit: Suitable for confidential  
medical data exchange - Limitations: Less decentralized than traditional blockchains  
Platform Performance Analysis  
Platform  
Throughput (TPS) Latency Energy Efficiency  
Privacy Features  
Limited  
Smart  
Support  
Contract  
Ethereu  
m
15  
15-30s  
2-5s  
Low  
High  
Comprehensive  
Hyperled 3000+  
Strong  
Chaincode  
ger  
Fabric  
Hyperled 1000+  
ger  
Sawtoot  
h
3-8s  
2-4s  
High  
High  
Moderate  
Excellent  
Transaction Processors  
Contracts  
R3  
500+  
Corda  
Major Challenges and Open Research Questions  
Scalability and Performance Challenges  
Transaction Throughput Limitations  
Current State: Most blockchain platforms struggle to handle the volume of medical data transactions required  
for large healthcare systems.  
Specific Issues: - Ethereum processes ~15 transactions per second - Medical facilities generate thousands of  
records daily - Real-time access requirements conflict with blockchain confirmation times  
Research Questions: - How can sharding techniques be adapted for medical data partitioning? - What are  
optimal hybrid architectures for high-throughput medical systems? - Can layer-2 solutions maintain security  
guarantees for sensitive medical data?  
Storage Scalability  
Challenges: - On-chain storage costs prohibitive for large medical files - Off-chain storage introduces new trust  
assumptions - Data availability guarantees in distributed storage systems  
Open Problems: - Optimal data partitioning strategies for medical information - Incentive mechanisms for off-  
chain storage providers - Cross-chain data availability and consistency  
Privacy and Security Challenges  
Privacy-Utility Trade-offs  
Fundamental Tension: Balancing data utility for medical research with individual privacy protection.  
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Specific Challenges: - Differential privacy parameter selection for medical data - Re-identification risks in  
anonymized medical datasets - Inference attacks on encrypted medical data  
Research Directions: - Adaptive privacy mechanisms based on data sensitivity - Privacy-preserving federated  
learning for medical AI - Homomorphic encryption optimization for medical computations  
Quantum Threat Considerations  
Emerging Concern: Quantum computers pose significant threats to current cryptographic schemes used in  
medical blockchain systems.  
Vulnerable Components: - RSA and ECC-based digital signatures - Current hash functions (SHA-256) -  
Classical encryption schemes  
Post-Quantum Solutions: - Lattice-based cryptography for medical data encryption - Hash-based signatures  
for blockchain integrity - Quantum key distribution for ultra-secure medical communications  
Regulatory and Compliance Challenges  
HIPAA Compliance  
Key Requirements: - Administrative safeguards for blockchain networks - Physical safeguards for node  
infrastructure - Technical safeguards for data transmission and storage  
Compliance Challenges: - Immutability conflicts with data correction requirements - Audit log accessibility  
and format requirements - Business associate agreements for blockchain participants  
GDPR and Data Protection  
Right to be Forgotten: - Blockchain immutability vs. data deletion requirements - Technical solutions:  
chameleon hashes, mutable blockchains - Legal interpretations of “erasure” in distributed systems  
Data Minimization Principle: - Storing minimal necessary data on blockchain - Purpose limitation for medical  
data processing - Consent management in distributed systems  
Interoperability and Integration Challenges  
Legacy System Integration  
Technical Challenges: - API compatibility with existing EHR systems - Data format standardization (HL7  
FHIR, DICOM) - Migration strategies for existing medical databases  
Organizational Challenges: - Change management in healthcare institutions - Staff training and adoption -  
Cost-benefit analysis for blockchain migration  
Cross-Chain Interoperability  
Current Limitations: - Isolated blockchain networks - Incompatible consensus mechanisms - Different  
cryptographic schemes  
Research Needs: - Universal medical data interchange protocols - Cross-chain atomic swaps for medical data -  
Standardized smart contract interfaces  
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Governance and Trust Challenges  
Decentralized Governance Models  
Key Questions: - How should healthcare blockchain consortiums make decisions? - What voting mechanisms  
are appropriate for medical data governance? - How to handle disputes in decentralized medical systems?  
Proposed Solutions: - Stakeholder-weighted voting systems - Medical ethics committee integration -  
Automated compliance checking through smart contracts  
Trust Establishment  
Multi-Party Trust: - Patients, providers, insurers, researchers, regulators - Different trust requirements and risk  
tolerances - Dynamic trust relationships based on context  
Technical Trust Mechanisms: - Reputation systems for healthcare participants - Cryptographic proof of  
compliance - Transparent audit mechanisms  
Future Directions and Research Opportunities  
Technical Research Directions  
Advanced Cryptographic Schemes  
Multiparty Computation (MPC) for Medical Data - Opportunity: Enable secure collaborative analysis of  
medical data across institutions - Research Needs: Efficient MPC protocols for large-scale medical datasets -  
Applications: Multi-institutional clinical trials, epidemiological studies  
Functional Encryption Advancements - Goal: Enable fine-grained computation on encrypted medical data -  
Challenges: Balancing functionality with security and efficiency - Potential: Personalized medicine without  
privacy compromise  
Quantum-Blockchain Integration  
Quantum Key Distribution (QKD) for Medical Networks - Vision: Ultra-secure key exchange for critical  
medical communications - Technical Hurdles: QKD network scalability and cost - Timeline: Practical  
implementation within 5-10 years  
Quantum-Enhanced Consensus Mechanisms - Concept: Quantum advantage for blockchain consensus -  
Research Areas: Quantum Byzantine agreement protocols - Long-term Impact: Exponentially faster  
consensus for medical blockchains  
System Architecture Evolution  
Hybrid Quantum-Classical Systems  
Architecture Vision: - Classical blockchain for routine operations - Quantum components for ultra-secure  
critical operations - Seamless integration between quantum and classical layers  
Research Priorities: - Quantum-classical interface protocols - Security analysis of hybrid systems - Cost-  
effectiveness evaluation  
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Neuromorphic Computing Integration  
Emerging Opportunity: Brain-inspired computing architectures for medical blockchain processing - Benefits:  
Ultra-low power consumption, adaptive processing - Applications: Real-time medical data analysis, pattern  
recognition - Research Stage: Early conceptual development  
Application Domain Expansion  
Precision Medicine and Genomics  
Genomic Data Blockchain Platforms - Challenges: Massive data volumes, long-term storage requirements -  
Opportunities: Secure genomic data marketplaces, personalized therapy platforms - Technical Needs:  
Specialized compression algorithms, efficient search mechanisms  
Pharmacogenomics Integration - Vision: Blockchain-secured personalized drug selection - Requirements:  
Integration with drug databases, regulatory compliance - Impact: Reduced adverse drug reactions, improved  
treatment outcomes  
Global Health and Pandemic Preparedness  
Pandemic Response Blockchain Networks - Purpose: Rapid, secure data sharing during health emergencies -  
Features: Emergency access protocols, international interoperability - Lessons from COVID-19: Need for pre-  
established data sharing frameworks  
Global Health Surveillance - Applications: Disease outbreak tracking, vaccine distribution monitoring -  
Technical Requirements: Real-time data processing, mobile device integration - Privacy Considerations:  
Balancing public health needs with individual privacy  
Standardization and Regulatory Evolution  
International Standards Development  
IEEE Standards for Medical Blockchain - Current Status: Working groups established - Scope: Technical  
specifications, security requirements, interoperability - Timeline: Initial standards expected by 2026  
HL7 FHIR Blockchain Integration - Goal: Seamless integration with existing healthcare standards - Progress:  
Pilot implementations underway - Impact: Accelerated blockchain adoption in healthcare  
Regulatory Framework Evolution  
Regulatory Sandboxes for Healthcare Blockchain - Purpose: Safe testing environment for innovative  
blockchain solutions - Participants: FDA, EMA, other regulatory bodies - Benefits: Accelerated innovation  
with maintained safety standards  
Cross-Border Regulatory Harmonization - Need: Consistent regulations for global healthcare blockchain  
networks - Challenges: Different privacy laws, healthcare systems - Approach: International cooperation  
frameworks  
Societal and Ethical Considerations  
Digital Health Equity  
Blockchain Accessibility - Challenge: Ensuring blockchain benefits reach underserved populations - Solutions:  
Mobile-first blockchain applications, offline capability - Research Needs: Low-resource blockchain  
implementations  
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Data Sovereignty - Indigenous Health Data: Respecting traditional data governance. National Data  
Sovereignty: Balancing global interoperability with local control - Technical Solutions: Sovereign blockchain  
networks, federated architectures  
Ethical AI-Blockchain Integration  
Algorithmic Fairness in Medical Blockchain - Concern: Biased AI decisions recorded immutably on  
blockchain - Solutions: Explainable AI, bias detection mechanisms Governance: Ethics committees for AI-  
blockchain systems  
Patient Agency and Control - Vision: True patient ownership of medical data - Technical Requirements:  
User-friendly interfaces, granular control mechanisms - Social Impact: Shift in healthcare power dynamics  
Economic and Business Model Innovation  
Tokenized Healthcare Ecosystems  
Health Data Tokenization - Concept: Patients earn tokens for contributing health data - Benefits: Incentivized  
participation, data quality improvement - Challenges: Regulatory approval, value determination  
Medical Research DAOs (Decentralized Autonomous Organizations) - Vision: Community-governed  
medical research funding - Mechanism: Token-based voting on research priorities - Potential: Democratized  
medical research funding  
Blockchain-Based Healthcare Insurance  
Parametric Insurance for Health Events - Automation: Smart contracts for automatic claim processing -  
Transparency: Immutable claim and payment records - Efficiency: Reduced administrative costs, faster  
payouts  
Risk Pool Tokenization - Innovation: Decentralized insurance risk sharing - Benefits: Lower costs, global risk  
distribution - Requirements: Regulatory frameworks for decentralized insurance  
CONCLUSION  
This comprehensive survey of blockchain-based secure storage schemes for medical information reveals a  
rapidly evolving field with significant potential to transform healthcare data management. Through our analysis  
of 140+ research papers spanning 2018-2025, several key findings emerge:  
KEY FINDINGS SUMMARY  
Architectural Convergence: The field has converged on hybrid architectures that combine on-chain metadata  
management with off-chain encrypted storage, typically using IPFS or cloud services. This approach  
successfully balances the immutability and transparency benefits of blockchain with the scalability requirements  
of medical data systems.  
Cryptographic Sophistication: Advanced cryptographic techniques, particularly attribute-based encryption  
(ABE), homomorphic encryption, and zero-knowledge proofs, have become integral to protecting sensitive  
medical information while enabling controlled sharing and computation.  
Platform Maturation: Permissioned blockchain platforms, especially Hyperledger Fabric and private Ethereum  
networks, have emerged as preferred choices for healthcare applications due to their superior privacy controls,  
scalability, and regulatory compliance capabilities.  
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Smart Contract Integration: Programmable smart contracts have proven essential for implementing  
sophisticated access control policies, consent management systems, and automated compliance checking in  
medical blockchain systems.  
Major Contributions of This Survey  
Our survey makes several significant contributions to the research community:  
1.  
2.  
Comprehensive Taxonomy: We present the first comprehensive classification framework for  
blockchain-based medical storage schemes, organizing approaches across architectural, privacy,  
platform, and application dimensions.  
Comparative Analysis: Our systematic comparison of different technical approaches, including  
performance benchmarks and security analysis, provides practical guidance for researchers and  
implementers.  
3.  
4.  
5.  
Challenge Identification: We identify and categorize major challenges including scalability limitations,  
privacy-utility trade-offs, regulatory compliance complexities, and interoperability barriers.  
Trend Analysis: Our analysis of recent advancements highlights emerging trends including post-  
quantum cryptography integration, AI-blockchain convergence, and digital twin implementations.  
Future Roadmap: We provide a comprehensive roadmap for future research directions, covering  
technical innovations, application domain expansion, and societal considerations.  
Final Remarks  
Blockchain technology represents a paradigm shift in medical data management, offering unprecedented  
opportunities to enhance security, privacy, and patient control while enabling new forms of collaborative  
healthcare delivery and research. However, realizing this potential requires continued research, careful  
implementation, and thoughtful consideration of technical, regulatory, and social challenges.  
The convergence of blockchain with emerging technologies such as artificial intelligence, quantum computing,  
and digital twins promises even more transformative possibilities for healthcare. As the field continues to mature,  
interdisciplinary collaboration between computer scientists, healthcare professionals, regulatory experts, and  
ethicists will be essential to ensure that blockchain-based medical storage systems serve the ultimate goal of  
improving human health outcomes.  
This survey provides a foundation for understanding the current state of the field and charting paths forward.  
We encourage researchers to build upon these findings, address the identified challenges, and explore the  
promising opportunities that lie ahead in blockchain-based secure storage for medical information.  
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[Azaria et al., 2016] A. Azaria, A. Ekblaw, T. Vieira, and A. Lippman, “MedRec: Using blockchain for  
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[Chenthara et al., 2020] S. Chenthara, K. Ahmed, H. Wang, F. Whittaker, and Z. Chen, “Healthchain: A  
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[Dubovitskaya et al., 2020] A. Dubovitskaya et al., “ACTION‑EHR: Patient‑centric blockchain‑based  
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