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Blockchain-enabled secure and efficient data sharing scheme for trust management in healthcare smartphone network
Rati Bhan1, Rajendra Pamula1, Parvez Faruki2
1Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, Dhanbad, 826004 India.
This study introduces a Hyperledger blockchain solution to detect compromised Internet of Medical Things (IoMT) devices in healthcare networks. The system enhances security and reliability for remote patient monitoring and data exchange.
Area of Science:
- Computer Science
- Cybersecurity
- Health Informatics
Background:
- The Internet of Medical Things (IoMT) enables remote patient monitoring but faces security risks from compromised devices.
- Healthcare Smartphone Networks (HSN) are vulnerable to data breaches via malicious IoMT nodes.
- Secure and trusted exchange of confidential patient records is crucial for remote healthcare.
Purpose of the Study:
- To propose a novel technique for identifying compromised IoMT nodes within HSNs.
- To enhance the security and privacy of sensitive patient health records.
- To improve the overall reliability and resilience of IoMT-based healthcare systems.
Main Methods:
- Implementation of a Hyperledger blockchain framework to detect malicious IoMT nodes.
- Development of a Clustered Hierarchical Trust Management System (CHTMS) for node blocking.
- Integration of Elliptic Curve Cryptography (ECC) for data protection and Denial-of-Service (DoS) resilience.
Main Results:
- The proposed blockchain-based system significantly improved the detection performance of compromised IoMT nodes.
- Evaluation demonstrated enhanced security and reliability compared to existing methods.
- The system effectively safeguards sensitive health records against unauthorized access.
Conclusions:
- Integrating blockchain technology into HSNs offers a robust solution for IoMT security.
- The CHTMS and ECC provide effective mechanisms for threat mitigation and data protection.
- The proposed approach enhances the trustworthiness of remote patient health monitoring systems.
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