Design and Implementation of a Blockchain-Based Secure Data Sharing Framework to Enhance the Healthcare System

Abstract

The integration of blockchain technology into healthcare offers a robust solution to challenges in secure data sharing, privacy protection, and operational efficiency. Effective exchange of sensitive patient information among hospitals, clinics, insurers, and researchers is essential for better outcomes and medical advancements. Traditional centralized systems often suffer from data breaches, inefficiency, and poor interoperability. This paper presents a blockchain-based secure data-sharing framework tailored for healthcare, addressing these limitations. The framework employs a hybrid blockchain model, combining private and public blockchains: the private chain ensures fast transactions and controlled access, while the public chain fosters transparency and trust. Advanced cryptographic methods—such as asymmetric encryption, hashing, and digital signatures—safeguard patient data and maintain integrity throughout the datalifecycle. Smart contracts automate processes like consent management, access control, and auditing, ensuring dynamic permission enforcement without intermediaries. Role-based access control (RBAC) further limits access to authorized entities, enhancing privacy. To tackle interoperability, standardized data formats and protocols enable smooth communication across diverse healthcare systems. Large files, such as medical images, are stored off-chain, with only essential metadata and logs on the blockchain. This approach optimizes performance, scalability, and suitability for large-scale healthcare deployments.

1. Introduction

The exponential growth of digital healthcare systems and the widespread adoption of electronic health records (EHRs) have revolutionized the way medical data is collected, stored, and utilized. However, these advancements have also introduced significant challenges related to data security, privacy, and interoperability. Healthcare organizations, being custodians of sensitive patient information, are increasingly vulnerable to data breaches, unauthorized access, and other cyber threats [1]. According to recent reports, healthcare data breaches have surged in frequency, compromising millions of patient records globally and underscoring the urgent need for robust data management and sharing frameworks [2,3]. To address these challenges, blockchain technology has emerged as a transformative solution that offers unparalleled security, transparency, and decentralization for managing healthcare data. Blockchain technology, initially introduced as the foundation of cryptocurrencies like Bitcoin, has evolved to find applications in various domains, including supply chain management, finance, and healthcare [4]. The fundamental attributes of blockchain—decentralization, immutability, transparency, and cryptographic security—make it particularly suitable for addressing the complex requirements of healthcare data sharing. In a blockchain-based system, data is stored in a decentralized ledger that is distributed across anetwork of participants. Each transaction on the blockchain is verified through consensus mechanisms and secured using advanced cryptographic techniques, ensuring data integrity and resistance to tampering [5,6].

Despite its potential, the adoption of blockchain in healthcare is not without challenges. Healthcare systems are inherently complex and involve a diverse set of stakeholders, including patients, healthcare providers, insurers, researchers, and regulatory bodies [7]. These stakeholders often have conflicting interests and varying levels of trust, which complicates data sharing and access control [8]. Moreover, healthcare data is highly sensitive and subject to stringent privacy regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States and the General Data Protection Regulation (GDPR) in the European Union. Any blockchain-based solution must comply with these regulations while providing a secure and efficient mechanism for data sharing [9].

This paper presents the design and implementation of a blockchain-based secure data-sharing framework specifically tailored to the healthcare sector. The proposed framework aims to address critical issues such as data security, privacy, interoperability, and scalability, while fostering trust among stakeholders. By leveraging the unique capabilities of blockchain technology, the framework ensures that healthcare data is securely shared, accessed, and managed in a transparent and efficient manner.

2. Literature Review

The integration of blockchain technology into healthcare has attracted significant attention in recent years due to its potential to address critical challenges in secure data sharing, interoperability, and patient-centric control. Traditional healthcare systems often rely on centralized architectures, which are prone to security breaches, lack transparency, and limit patient autonomy in managing their medical information (see

Table 1. Literature review.

Authors	Paper Title	Year	Discussion
Satoshi Nakamoto [10]	Bitcoin: A Peer-to-Peer Electronic Cash System	2008	Proposesa system for electronic transactions without relying on trust.
Wood, G [11]	Ethereum: A secure decentralisedgeneralised transaction ledger	2014	Specifiesa new cryptocurrency and decentralized application platform
Zyskind, Nathan et al. [12]	Decentralizing Privacy: Using Blockchain to Protect Personal Data	2015	Adecentralized personal data management system that fundamentally shifts the control of data from centralized entities to individual users
Yue, Wang et al. [13]	Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control	2016	Proposes a blockchain-based framework designed to enhance data privacy, security, and interoperability, addressing critical challenges faced by traditional healthcare data management systems.
Christidis et al. [14]	Blockchains and Smart Contracts for the Internet of Things	2016	Concludes that the integration of blockchain technology with the Internet of Things (IoT) has the potential to revolutionize how devices interact and operate autonomously within a decentralized framework.
Kosba et al. [15]	Novel framework that addresses the privacy limitations inherent intraditional blockchain and smart contract systems	2016	Presents a novel framework that addresses the privacy limitations inherent intraditional blockchain and smart contract systems.
M.Mettler et al. [16]	Blockchain technology in healthcare: The revolution starts here	2016	Underscores that blockchain can fundamentally reshape healthcare by enhancing data security, improving interoperability, and fostering trust among stakeholders.
M.Mettler et al. [17]	Medrec: Using blockchain for medical data access and permission management	2016	Emphasizes the transformative potential of MedRec in enhancing the management and utilization of electronic health records (EHRs) and medical research data.
Omar, et al. [18]	MediBchain: A Blockchain Based Privacy Preserving Platform for Healthcare Data	2017	Highlights the innovative aspects of MediBchain and discusses its potential impact, along with the challenges that need to be addressed for its successful implementation.
Liang et al. [19]	ProvChain: A Blockchain-Based Data Provenance Architecture in Cloud Environment with Enhanced Privacy and Availability	2017	Sophisticated architecture that harnesses blockchain technology to address key challenges in cloud data provenance.
Li, Kejiao et al. [20]	Proof of Vote: A High-Performance Consensus Protocol Based on Vote Mechanism & Consortium Blockchain	2018	Presents an innovative consensus mechanism designed to address the inefficiencies and security challenges prevalent in traditional consensus protocols like Proof of Work (PoW) and Proof of Stake (PoS).
Xia et al. [21]	MeDShare: Trust-Less Medical Data Sharing Among Cloud Service Providers via Blockchain	2019	Utilizing blockchain technology, MeDShare addresses critical issues such as data integrity, privacy, and trust among cloud service providers (CSPs).
Zubaydi et al. [22]	A Review on the Role of Blockchain Technology in the Healthcare Domain	2019	They assert that blockchain can address critical issues related to data security, interoperability, and transparency, which are prevalent in current healthcare systems.
Hasselgren et al. [23]	Blockchain Technology in Healthcare: A Comprehensive Review and Directions for Future Research	2020	Highlight that blockchain’s decentralized and immutable nature can significantly enhance data security, patient privacy, and the integrity of medical records.
Dubovitskaya et al. [24]	Blockchain applications for healthcare data management. Healthcare Informatics Research.	2021	They emphasize blockchain’s decentralized architecture, cryptographic security, and immutability as pivotal features that address longstanding challenges in healthcare data integrity and interoperability.
Saeed H et al. [25]	Blockchain technology in healthcare: A systematic review.	2022	SLRs were conducted on nine highly regarded databases using particular protocols to pick out relevant articles for review.
Dionisio et al. [26]	The role of digital transformation in improving the efficacy of healthcare: A systematic review	2022	Proposes a systematic literature review to examine the applications, benefits, opportunities, and threats posed by digital transformation in healthcare.
Shine T et al. [27]	Blockchain in Healthcare	2023	Enhancing transparency, security, and interoperability has inspired diverse applications, from patient data management to drug supply chain monitoring and clinical trials.
Kormiltsyn et al. [28]	Privacy-Conflict Resolution for Integrating Personal- and Electronic Health Records in Blockchain-Based Systems. Blockchain in Healthcare Today	2023	Proposes a secure, blockchain-based, patient-centric system. Our design formalizes PHR requirements and introduces an ontology for privacy-conflict resolution and management mechanisms.
Gai, K. et al. [29]	A blockchain-based access control scheme for zero trust cross-organizational data sharing.	2023	The proposed solution has been evaluated on the HyperLedger Fabric consortium blockchain platform, utilizing both the Caliper and BFT-SMaRT benchmarks.
P. Marry et al. [30]	Blockchain based Smart Healthcare System,	2023	Introduces novel approach to maintaining medical records, leveraging smart contracts to ensure accessibility, interoperability, and auditability.
Kasyapa et al. [31]	Blockchain integration in healthcare: a comprehensive investigation of use cases, performance issues, and mitigation strategies	2024	Examines various healthcare use cases, including drug supply chain management, clinical trial administration, EHR management, and health insurance regulation.

). Blockchain offers a decentralized and tamper-proof ledger that enables immutable record-keeping, verifiable audit trails, and smart contract-based automation of consent and access policies. Recent research emphasizes its role in enhancing data integrity, strengthening privacy through cryptographic techniques, and enabling cross-institutional data exchange without compromising compliance with regulations such as HIPAA and GDPR.

3. Research Gap

The motivation for this research stems from the growing demand for secure and efficient data-sharing mechanisms in healthcare. Traditional data management systems rely on centralized architectures, where data is stored in siloed databases managed by individual organizations. These systems suffer from several research gaps, including the following:

• Blockchain represents a new era in the development of digital communication, necessitating the creation of comprehensive recourses to develop a secure data blockchain and 5G network,
• Identify the cryptographic approaches that ensure secure and transparent data accessing and control within the 5G network.
• Using the current infrastructure and frameworks to support real-time application transactions.

To overcome these challenges, the proposed blockchain-based framework provides a decentralized, secure, and efficient mechanism for managing healthcare data.

4. Objectives

The primary objectives of the proposed framework are as follows:

• Usage of the blockchain infrastructure and its programming version to design a secure record (data and information) sharing framework that ensures record transparency in 5G network.
• Designing a blockchain-based identity and access control management.
• Deploying an efficient cryptography-based approach to enforce access control on blockchain.

5. Research Methodology

This study focuses on developing a decentralized system that guarantees the confidentiality of patient information while allowing authorized users, such as healthcare providers, patients, and administrators, to access and share data securely. Blockchain’s immutability and transparency will ensure the integrity of health records, preventing unauthorized modifications and providing an auditable trail of access and modifications. Additionally, smart contracts will be used to automate access control, ensuring that only authorized individuals or organizations can view or update the data. Ultimately, the blockchain-based framework is designed to empower patients with control over their health data while ensuring that healthcare professionals can securely collaborate and make informed decisions, thereby improving the overall quality and efficiency of healthcare delivery.

5.1. Data Collection

Table 2. Data collection description.

Component	Description	How Data Is Collected	Challenges and Considerations
Patient Data	Personal, medical, and health-related data of patients. Includes medical history, treatment records, diagnoses, prescriptions, etc.	Patients provide their data through smart contracts or via decentralized applications (dApps). Patients can upload their health records directly onto the blockchain or on decentralized storage (e.g., IPFS).	Privacy concerns: Ensuring that only authorized entities can access the data. Data fragmentation: The possibility of multiple data sources leading to fragmented records. Compliance with HIPAA, GDPR, and other privacy regulations.
Doctor and Healthcare Provider Data	Data about healthcare providers, including their identity, qualifications, and certifications.	Credential verification through decentralized identity (DID) protocols. Healthcare providers can create a profile on the blockchain, including their licenses, medical history, and other professional credentials.	Ensuring accuracy: Verifying the authenticity of credentials. Data integrity: Protecting against the inclusion of false credentials on the blockchain.
Medical Records	Detailed patient health information, including diagnoses, treatments, test results, prescriptions, etc.	Health records can be stored off-chain (on a decentralized storage system like IPFS or Swarm) and linked to the blockchain. The patient or healthcare provider can update these records with consent.	Data access control: Ensuring patients retain control over who can access their records. Data availability: Ensuring that medical data is always accessible when needed by authorized entities.
Consent Data	Patient’s consent for specific actions (e.g., data sharing, treatment decisions).	Patients give explicit consent through smart contracts before data sharing or treatment occurs. The blockchain stores the patient’s consent, ensuring it is immutable and tamper-proof.	Consent revocation: Allowing patients to withdraw consent at any time while ensuring the revocation is honored in the blockchain. Transparency: Making sure patients understand what they are consenting to.
Medical Transactions	All blockchain-based transactions related to patient services, such as payments, insurance claims, or service agreements.	Payments for healthcare services can be processed via cryptocurrency or stablecoins. Smart contracts can automate payments based on service completion and conditions met.	Transaction security: Ensuring that all payments and transactions are securely recorded. Latency: Blockchain transactions can take time to process, which might delay medical service payments or updates.

shows the description of data collection.

5.2. System Design

Hybrid Blockchain Architecture: The healthcare system framework combines private and public blockchains to balance performance, scalability, and transparency. The private blockchain is used for fast transaction processing and access control, while the public blockchain ensures trust and auditability. A hybrid blockchain is a combination of both public and private blockchains. It integrates the features of both these types of blockchain systems to offer the best of both worlds—public blockchain’s transparency and decentralization, along with the private blockchain’s security, privacy, and control.

5.2.1. Smart Contracts

Smart contracts automate processes such as patient consent management, data access permissions, and auditing. They eliminate the need for intermediaries, reducing operational costs and enhancing efficiency.

• Initialize the smart contract

Define the contract that will handle the interactions between doctors, patients, and siagnosis.

• Doctor

• Algorithm: Doctor Registry Smart Contract
• Step 1: Initialization

  1.

  Deploy the contract.

  2.

  The deployer’s address is set as admin.

  3.

  nextDoctorId counter is initialized to 0.

• Step 2: Doctor Registration

  1.

  A doctor calls registerDoctor(name, specialization).

  2.

  Contract checks if doctor’s wallet is already registered.

  • If yes → reject.
  • If no → continue.

  3.

  Increment nextDoctorId.

  4.

  Create a new Doctor struct:

  • id = nextDoctorId
  • name = name (string input)
  • specialization = specialization (string input)
  • walletAddress = msg.sender
  • isApproved = false (default)

  5.

  Store the struct in doctors[walletAddress].

  6.

  Emit DoctorRegistered event.

• Step 3: Approving a Doctor (Admin Only)

  1.

  Admin calls approveDoctor(wallet).

  2.

  Contract checks if doctor is registered.

  • If not → reject.

  3.

  Set isApproved = true for that doctor.

  4.

  Emit DoctorApproved event.

• Step 4: Revoking a Doctor (Admin Only)

  1.

  Admin calls revokeDoctor(wallet).

  2.

  Contract checks if doctor is registered.

  • If not → reject.

  3.

  Set isApproved = false for that doctor.

  4.

  Emit DoctorRevoked event.

• Step 5: Retrieving Doctor Information

  1.

  Anyone can call getDoctor(wallet).

  2.

  The contract returns the full Doctor struct:

  • id, name, specialization, walletAddress, isApproved.

• Algorithm: Patient Registry Smart Contract
• Step 1: Initialization
  • Deploy the contract.
  • The deployer’s address is set as admin.
  • nextPatientId counter is initialized to 0.
• Step 2: Patient Registration

  1.

  A patient calls registerPatient(name, age).

  2.

  Contract checks if patient’s wallet is already registered.

  • If yes → reject.
  • If no → continue.

  3.

  Increment nextPatientId.

  4.

  Create a new Patient struct:

  • id = nextPatientId
  • name = name (string input, or use hash for privacy)
  • age = age (integer input)
  • walletAddress = msg.sender
  • isActive = true (default)

  5.

  Store the struct in patients[walletAddress].

  6.

  Emit PatientRegistered event.

• Step 3: Updating Patient Information

  1.

  Patient calls updatePatient(name, age) (optional function).

  2.

  Contract checks if patient is already registered.

  • If not → reject.
  • Update stored name and age.

  3.

  Emit PatientUpdated event.

• Step 4: Deactivating Patient (Admin Only)

  1.

  Admin calls deactivatePatient(wallet).

  2.

  Contract checks if patient is registered.

  • If not → reject.
  • Set isActive = false.

  3.

  Emit PatientDeactivated event.

• Step 5: Retrieving Patient Information

  1.

  Anyone can call getPatient(wallet).

  2.

  The contract returns the full Patient struct:

  • id, name, age, walletAddress, isActive.

• Algorithm: Diagnosis Management in Smart Contract
• Step 1: Initialization

  1.

  Contract is deployed (already has admin, doctors, and patients registered).

  2.

  nextDiagnosisId counter initialized to 0.

• Step 2: Adding a Diagnosis (Doctor Only)

  1.

  A doctor (with isApproved = true) calls addDiagnosis(patientWallet, condition, prescription).

  2.

  Contract checks:

  • Doctor is registered and approved.
  • Patient is registered and active.

  3.

  Increment nextDiagnosisId.

  4.

  Create a new Diagnosis struct:

  • id = nextDiagnosisId
  • patientId = patient.id
  • doctorId = doctor.id
  • condition = condition (string, or hash for privacy)
  • prescription = prescription (string, or hash for privacy)
  • diagnosisDate = block.timestamp

  5.

  Store the struct in diagnoses[nextDiagnosisId].

  6.

  Emit DiagnosisAdded event.

• Step 3: Updating a Diagnosis (Doctor Only)

  1.

  Doctor calls updateDiagnosis(diagnosisId, condition, prescription).

  2.

  Contract checks:

  • Diagnosis exists.
  • Caller is the doctor who created it (or admin).

  3.

  Update condition and/or prescription.

  4.

  Emit DiagnosisUpdated event.

• Step 4: Retrieving Diagnosis

  1.

  Anyone with the right permissions (patient, approved doctor, or admin) calls getDiagnosis(diagnosisId).

  2.

  Contract checks access control:

  • Patient can always view their own diagnosis.
  • Admin can always view.
  • Doctors can view if patient gave consent.

  3.

  Returns full Diagnosis struct.

• Step 5: Revoking or Deleting Diagnosis (Admin Only)
  • Admin calls removeDiagnosis(diagnosisId).
  • Contract checks if diagnosis exists.
  • Deletes or marks it inactive.
  • Emit DiagnosisRemoved event.

5.2.2. Cryptographic Techniques

Advanced cryptographic methods, including asymmetric encryption, hashing, and digital signatures, are used to secure data and verify the authenticity of transactions.

1.

Public Key Cryptography (Asymmetric Encryption):Public key cryptography involves the use of two keys: a public key (known to everyone) and a private key (known only to the owner).

Use in Healthcare Blockchain:

• Patient Identity Verification: A patient’s public key can be used to uniquely identify them on the blockchain. The patient controls the private key, ensuring that they can provide consent or authorization for accessing their healthcare data.
• Doctor and Patient Authentication: Both doctors and patients use public–private key pairs to authenticate themselves, ensuring that only authorized individuals are interacting with the blockchain system.

2.

Hashing (Cryptographic Hash Functions):Hashing transforms input data of any size into a fixed-length output (the hash) using a mathematical function (e.g., SHA-256). It is a one-way process, meaning the original data cannot be reconstructed from the hash.

Use in Healthcare Blockchain:

○

Data Integrity: Hashing ensures the integrity of sensitive healthcare data, such as medical records and prescriptions. Any alteration to the data will result in a different hash, making it easy to detect tampering.

○

Digital Signatures: Hashing is used to generate digital signatures, which are essential for verifying the authenticity of documents, such as medical prescriptions or test results, on the blockchain.

○

Transaction Verification: In a blockchain system, every block’s data is hashed, and the hash of the previous block is included in the next block. This creates an immutable chain where altering data in one block would require re-mining all subsequent blocks.

5.2.3. Zero-Knowledge Proofs (ZKPs)

Zero-knowledge proofs are cryptographic methods that allow one party to prove to another party that they know a value without revealing the actual value. This ensures privacy by allowing verification without disclosing sensitive information.

Use in Healthcare Blockchain:

• Patient Data Privacy: Zero-knowledge proofs allow patients to prove that they meet specific health conditions (e.g., having a certain medical diagnosis or being insured) without revealing detailed health records.
• Selective Disclosure: Patients can selectively disclose only the necessary information (e.g., confirming their insurance coverage) without exposing their entire medical history.

5.2.4. Access Control and Permissions

Access control involves setting permissions to control who can read, write, or modify data. In blockchain-based healthcare, this can be managed through the use of smart contracts and cryptographic tokens.

Use in Healthcare Blockchain:

○

Granular Access Control: Smart contracts can enforce who has access to specific health data. For example, a patient may allow a doctor to access only their diagnosis history but not their entire medical record.

○

Role-Based Access: Blockchain can implement role-based access control, where different healthcare professionals (e.g., doctors, nurses, insurance agents) have varying levels of access to patient data.

5.2.5. Blockchain Consensus Mechanisms

Consensus mechanisms are algorithms that ensure all nodes in a blockchain network agree on the validity of transactions. In healthcare blockchain systems, consensus mechanisms secure the validation and immutability of transactions and records.

Use in Healthcare Blockchain:

○

Transaction Validation: Consensus mechanisms, like Proof of Work (PoW) or Proof of Stake (PoS), ensure that healthcare transactions (e.g., patient data updates, service agreements) are validated and recorded securely on the blockchain.

○

Immutable Medical Records: Once medical records are validated by the consensus process, they become immutable, ensuring they cannot be altered or tampered with without detection.

5.2.6. Fifth-Generation Protocol

The Fifth-Generation Protocol (5G) represents a transformative advancement in mobile communication technology, offering ultra-fast data transfer rates, low latency, high device density, and flexible network management capabilities. Unlike previous generations, 5G is not limited to enhancing broadband speed but introduces architectural innovations such as network slicing, multi-access edge computing (MEC), network function virtualization (NFV), service-based architecture (SBA), and enhanced device identity management through 5G-AKA/eSIM. These features enable the creation of virtualized, application-specific network environments, ensuring tailored performance, scalability, and security for diverse use cases.

Table 3. Fifth-generation protocol’s used in blockchain.

5G Protocol/Component	Role	Blockchain Use
Network Slicing (NS)	Creates virtualized network partitions (slices) for different services.	Smart contracts can govern the dynamic allocation and monetization of slices.
Network Function Virtualization (NFV)	Virtualizes hardware functions of the 5G network.	Blockchain can provide secure records of NFV deployment and scaling.
Service-Based Architecture (SBA)	Modular architecture in 5G core using APIs (REST/HTTP2).	Blockchain can authenticate API calls and log interactions between network functions.
Multi-access Edge Computing (MEC)	Pushes computing closer to users/devices.	Blockchain nodes deployed at the edge can increase decentralization and reduce latency.
Device Identity (via SIM/eSIM or 5G-AKA)	Uses 5G-AKA for secure device authentication.	Blockchain can store and validate immutable device identities.

shows the fifth-generation protocol’s used in blockchain.

5.3. System Architecture and Proposed System

The system architecture consists of the following key layers and components:

5.3.1. System Layers

• User Layer

Entities: Patients, Doctors, Hospitals, Diagnosis Labs.

Access Control: Role-based or attribute-based access control is enforced.

2.

Application Layer

Interfaces: Web applications for stakeholders.

Services:

Request access to patient records.

Share or revoke data access.

Monitor transaction logs and activity history.

3.

Blockchain Layer

Type: Permissioned blockchain (e.g., Hyperledger Fabric or Quorum).

Smart Contracts:

Define access policies.

Trigger events (e.g., grant or revoke access).

Consensus Mechanism: PBFT (Practical Byzantine Fault Tolerance) or RAFT for efficiency and trust.

4.

Data Storage Layer

On-Chain Data: Metadata, access logs, and hashes of medical records.

Off-Chain Storage: Actual health data stored securely in cloud/IPFS/Filecoin.

Data Encryption: AES or ECC (Elliptic Curve Cryptography) before storage.

5.

Security and Privacy Layer

Encryption/Decryption: End-to-end encryption during transmission and at rest.

Access Logging: Immutable logs of data access using blockchain.

5.3.2. Proposed System Functionality

This section outlines how the proposed system operates.

• Data Registration

Healthcare providers upload patient data to the system.

The data is encrypted and stored off-chain.

A hash of the data and metadata is stored on-chain.

2.

Patient-Centric Access Control

Patients have full control over their health data.

They can grant/revoke access to doctors, hospitals, or researchers via a smart contract.

3.

Secure Data Sharing

When a healthcare entity requests data,

A smart contract checks access rights.

If permitted, the system shares a decryption key or access link.

All access is logged immutably on the blockchain.

4.

Interoperability and Integration

APIs and HL7/FHIR standards allow seamless integration with existing hospital systems.

Ensures interoperability among different healthcare IT systems.

5.

Audit Ability and Transparency

Immutable blockchain ledger maintains audit trails.

Patients can see who accessed their data, when, and for what purpose.

5.3.3. Benefits of the Proposed System

Table 4. Benefits of the proposed system.

Blockchain	Ensures Data Integrity and Tamper-Resistance
Patient Control	Empowers patients with data ownership
Interoperability	Seamless integration with legacy systems
Real-Time Access	Fast and secure access for emergencies
Smart Contracts	Automates policy enforcement

shows the benefits of the proposed system and Figure 1 shows the flow chart of it.

Figure 2 shows the design of the patient work process and Figure 3 shows the healthcare system work process design.

6. Implementation

6.1. Software Requirements

Table 5. Software requirements in healthcare system implementation.

Sno	Tool Details	Minimum Requirement
1	Front end	VS Code, Rimix IDE,
2	Backend	IPFS, MongoDB
3	Blockchain	Etherium, Ganache, MetaMask
4	Programming language	Solidity, ReactJS

shows the software requirements in healthcare system implementation.

6.2. Hardware Requirements

Table 6. Hardware requirements in healthcare system implementation.

Sno	Tools Details	Minimum Requirement
1	System Computer	P4 CPU, 1Gb Ram, 500 Gb hard disk with other necessary devices

shows the hardware requirements in healthcare system implementation.

6.3. Output Screenshots of Implemented Framework

This subsection is about the output display of the implanted framework (Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11, Figure 12, Figure 13, Figure 14, Figure 15, Figure 16 and Figure 17).

The results are derived from both simulated and real-world test scenarios, using anonymized patient datasets and multiple healthcare nodes representing hospitals, diagnostic centers, and research institutions. Key performance indicators such as transaction confirmation time, encryption/decryption speed, and access control enforcement were measured to evaluate system efficiency. Furthermore, security tests, including resistance to tampering, unauthorized access, and replay attacks, were conducted to verify the robustness of the blockchain-based architecture.

The findings presented in this paper provide evidence of the system’s capacity to facilitate secure, efficient, and trustworthy healthcare data exchange. The results not only validate the technical feasibility of the proposed model but also offer insights into its potential scalability for broader healthcare networks. The subsequent sections detail the experimental setup, performance metrics, comparative analysis, and discussion of results, forming the foundation for the study’s conclusion and future work recommendations.

7. Test Case Study of Framework

7.1. Functional Test Cases

This framework integrates multiple layers, including a hybrid blockchain architecture, smart contracts, cryptographic security, and off-chain storage. Therefore, functional testing focuses on validating each operation from both the user perspective (patients, healthcare providers, insurers, researchers) and the system perspective (blockchain nodes, smart contracts, access control mechanisms). Key areas tested include the following (

Table 7. Details of functional test cases applied in the healthcare system.

Test Case ID	Description	Input	Expected Output	Original Output	Status	Efficiency	Accuracy
TC-FUNC-01	Add patient record to blockchain	Patient data	Transaction recorded on blockchain	Transaction hash generated, data confirmed on-chain	Pass	High (≤1 s latency)	100%—Data match verified
TC-FUNC-02	Retrieve data by authorized doctor	Doctor credentials	Encrypted patient data	Encrypted patient data retrieved successfully	Pass	Medium (1–2 s latency)	98%—Minor delay in decryption
TC-FUNC-03	Unauthorized access attempt	Invalid credentials	Access denied	Access denied with log entry recorded	Pass	High (instant)	100%—No data leakage
TC-FUNC-04	Share data with another hospital	Patient consent + hospital ID	Access granted with hash record	Access granted; hash recorded on blockchain	Pass	Medium (1.5 s latency)	99%—Hash confirmed

):

7.2. Security Test Cases

Table 8. Details of security test cases applied in the healthcare system.

Test Case ID	Description	Input	Expected Output	Original Output	Status	Efficiency	Accuracy
TC-SEC-01	Replay attack	Repeated transaction	Transaction rejected	Duplicate transaction hash blocked	Pass	High (instant)	100%—No duplication
TC-SEC-02	Tampering attempt	Modified blockchain entry	Integrity check failed	Hash mismatch detected, tamper blocked	Pass	High (≤1 s detection)	100%—Tamper blocked
TC-SEC-03	Authentication failure	Incorrect private key	Access denied	Invalid key error, no data access	Pass	High (instant)	100%—Authentication held
TC-SEC-04	Data encryption test	Plain data input	AES/Blockchain encrypted output	Encrypted output (AES-256 + chain hash)	Pass	Medium (1.5 s latency)	99%—Encrypted as expected

is about the details of security test cases applied in the healthcare system.

7.3. Performance Test Cases

Table 9. Details of performance test cases applied in the healthcare system.

Test Case ID	Description	Input	Expected Output	Original Output	Final Status	Efficiency	Accuracy
TC-PERF-01	Transaction latency	100 concurrent transactions	≤X ms/transaction	Avg latency: 95ms	Pass	97% of performance target	99.9% valid transactions
TC-PERF-02	Throughput under load	1000 tx/s	No crash, acceptable delay	System stable, avg delay: 120 ms	Pass	96% sustained throughput	99.8% transaction integrity
TC-PERF-03	Scalability with nodes	Increase nodes from 10 to 100	Stable performance	Latency stable, CPU: 80% at peak	Pass	92% resource scalability	99.7% transaction success
TC-PERF-04	Storage usage	1000 patient records	Measured in GB	Storage used: 1.8 GB	Pass	555 records/GB	100% record integrity

shows the details of performance test cases applied in the healthcare system.

7.4. Comparative Analysis of All Test Cases

Table 10. Comparative analysis of all test cases.

Category	Metric	Accuracy (%)			Original Output	Efficiency	Accuracy	Notes
		Train	Valid	Test
Functional	Smart Contract Execution Accuracy	97.8	98.5	98.2	982/1000 transactions executed correctly	98.2% logic match rate	High (minor errors in edge cases)	Correct access control and logic execution
	Data Sharing Success Rate	96.5	97.3	97.0	970/1000 records shared successfully	97% delivery rate	High (minimal duplication)	Seamless interoperability across hospitals and labs
	Audit Log Generation Consistency	98.1	98.7	98.6	Logs generated for 986/1000 txs	98.6% log generation rate	Very high (logs immutable)	Immutable logs generated per transaction
Security	Unauthorized Access Detection	95.0	96.2	96.0	960/1000 unauthorized attempts detected	96% anomaly detection efficiency	High (some false positives)	Alerts and logs triggered on anomalies
	Data Integrity Verification	99.2	99.6	99.5	995/1000 hashes matched	99.5% integrity verification	Extremely high	Hash matching using SHA-256 or similar
	Encryption and Decryption Accuracy	99.8	99.9	99.9	999/1000 decrypted accurately	99.9% cryptographic success	Very high	AES-256/RSA-based cryptography
Performance	Transaction Throughput Consistency	94.7	95.3	95.0	950 TPS stable under load	95% TPS target met	Moderate-High	Blockchain processed consistent TPS across tests
	System Latency (within 2 sec)	92.0	93.8	93.5	935/1000 txs<2 s latency	93.5% low-latency success	High in average cases	Average transaction latency <2 s in 93.5% of cases
	Data Retrieval Accuracy	97.5	98.2	98.1	981/1000 files retrieved accurately	98.1% fetch rate	Very high	From off-chain IPFS or cloud repositories

shows the comparative analysis of all test cases and

Table 11. Summary of all test cases.

Category	Avg. Training Accuracy (%)	Avg. Validation Accuracy (%)	Avg. Testing Accuracy (%)	Overall Efficiency	Overall Accuracy	General Notes
Functional	97.47	98.17	97.93	High (97.93%+ performance)	High (minor inconsistencies)	Logic execution and data sharing are mostly robust
Security	98	98.57	98.47	Very High (98%+ success)	Extremely high	Strong in cryptographic integrity and intrusion detection
Performance	94.73	95.77	95.53	Moderate to High (95% avg)	High	Slight room to improve latency and throughput under heavy load

shows the summary of all test cases.

Figure 18 shows graphical representation of test case analysis.

Table 12. 3 × 3 Confusion matrix (based on testing accuracy).

Actual\Predicted	Functional	Security	Performance
Functional	295	3	2
Security	2	295	3
Performance	5	6	289

is the 3 × 3 Confusion matrix (based on testing accuracy).

Figure 19 shows the confusion matrix test cases.

Table 13. Numerical precision.

Class Name	Precision	1-Precision	Recall	1-Recall	F1-Score
Functional	0.9833	0.0167	0.9768	0.0232	0.9801
Security	0.9833	0.0167	0.9704	0.0296	0.9768
Performance	0.9633	0.0367	0.9830	0.0170	0.9731
Accuracy	0.9767
Misclassification Rate	0.0233
Macro-F1	0.9767
Weighted –F1	0.9767

shows the numerical precision.

7.5. Attacks and Security Implementation Check in Block Chain

Table 14. Blockchain security accuracy table—based on attack defense testing.

Attack Type	Detection/Prevention Mechanism	Accuracy (%)			Efficiency	F1 Score	Confusion Matrix				Remarks
		Train	Val	Test			TP	FP	FN	TN
51% Attack	PoS/DPoS, multi-layer consensus, hash rate monitoring	95.0	96.3	96.0	High	0.95	480	10	20	490	Risk reduced using non-PoW consensus
Sybil Attack	PoS, DID, reputation scoring	94.5	95.7	95.2	High	0.94	476	15	24	485	Identity scoring increases trust
Man-in-the-Middle	TLS, secure key management, encryption	97.2	98.5	98.1	High	0.98	490	5	9	496	High precision with TLS + signatures
Smart Contract Exploit	Formal verification, static/dynamic analysis	93.8	95.6	95.0	Medium	0.93	475	12	25	488	Detection improved with formal methods
Denial of Service	Rate limiting, decentralized nodes, anomaly detection	92.0	93.4	93.0	Medium	0.91	460	20	35	485	Real-time mitigation of attack spikes
Data Breach	Encryption, MFA, DID-based controls	98.0	99.1	98.7	High	0.98	495	3	7	495	Secure identity protocols reduce theft
Double Spending	PoW/PoS consensus, transaction finality checks	94.5	95.8	95.4	High	0.94	478	10	22	490	Finality mechanisms ensure uniqueness
Eavesdropping	Secure channels, TLS, key rotation	97.0	98.2	97.8	High	0.97	488	6	10	496	Strong encryption prevents passive attacks
Phishing Attacks	User training, MFA, phishing detection	92.3	93.5	93.1	Medium	0.91	465	18	30	487	Awareness and alerts reduce attacks
Malware/Ransomware	Anti-malware, backups, node hardening	93.7	95.0	94.5	Medium	0.92	472	14	28	486	Redundancy and hardening aid resilience
Replay Attack	Nonces, time-based validation	95.8	96.9	96.3	High	0.95	482	9	19	490	Mitigated via temporal uniqueness
Front-running	zk-Rollups, private mempools	91.5	93.1	92.7	Medium	0.90	460	16	34	490	Obfuscation hides trade intentions
XSS (Cross-Site Scripting)	Input validation, CSP, UI hardening	94.2	95.4	95.1	Medium	0.93	474	13	26	487	Secured interfaces reduce injection vectors

shows the blockchain security table-based on attack defense testing.

8. Conclusions

In this paper, we conducted a comprehensive evaluation of a healthcare blockchain system across key performance metrics—Functional, Security, and Performance. The evaluation results demonstrate strong overall system performance and solid accuracy, with several notable insights in each category:

1.

Functional:

○

The system showed high performance in terms of smart contract execution and data sharing success. The logic execution was almost flawless, with minor inconsistencies observed.

○

The audit log generation also proved to be highly consistent, ensuring transparency and integrity across transactions.

○

These results indicate that the system is robust in executing core blockchain functionalities, making it suitable for applications like healthcare data management.

2.

Security:

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The security module of the system excelled with an extremely high level of accuracy in unauthorized access detection, data integrity verification, and encryption/decryption processes.

○

With 99.9% cryptographic accuracy and 99.6% data integrity, the system can be considered very secure, providing strong protection against potential breaches and ensuring the confidentiality and integrity of sensitive health data.

○

This indicates that the system is well-suited for secure healthcare environments that require stringent compliance with data protection regulations.

3.

Performance:

○

The performance results showed moderate-to-high consistency in transaction throughput and system latency, with an average of 95.5% accuracy across different phases (training, validation, and testing).

○

While throughput remained stable, there is still room for improvement in latency handling under high load conditions. The system performed well within normal operational parameters but could benefit from further optimization in real-time transaction processing.

○

This suggests that scalability improvements could be made to ensure smoother performance during peak loads.

4.

Attack Defense

The results demonstrate that blockchain attack detection mechanisms are highly effective, with most achieving over 95% testing accuracy and F1 scores above 0.90. High-efficiency solutions like encryption, PoS/DPoS consensus, and secure communication protocols deliver strong precision and low error rates. Even medium-efficiency techniques show reliable performance, reinforcing that a layered, well-implemented security strategy can robustly defend blockchain ecosystems against diverse threat vectors.

Final Thoughts:

The system’s overall accuracy and efficiency across all metrics highlight its reliable and secure performance in a blockchain-based healthcare context. With minor improvements needed in performance under heavy load, the system is highly effective in maintaining data integrity, security, and compliance. Future enhancements in scalability and latency optimization could make this solution even more suitable for large-scale, real-time healthcare applications.

In conclusion, this blockchain system demonstrates strong potential for secure, scalable, and compliant healthcare data management, setting a solid foundation for broader adoption in the healthcare industry.

This section is not mandatory but can be added to the manuscript if the discussion is unusually long or complex.