Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/6731
Title: Blockchain-based secure framework for efficient management of IoT generated healthcare data
Authors: Sharma, Aashima
Supervisor: Kaur, Sanmeet
Singh, Maninder
Keywords: Blockchain;Internet of Medical Things;Healthcare;Privacy;Remote Patient Monitoring
Issue Date: 21-May-2024
Abstract: In recent years, the Internet of Medical Things (IoMT) has played a significant role in the healthcare industry. It has not only empowered medical services to handle complex real-time functions but has also greatly enhanced patient monitoring, benefitting patient care and medical research. Hence, there is a need to ensure that the data received from different sensors stays secure. In light of these advancements in the healthcare industry, concerns have arisen regarding the protection of sensitive medical data within the IoMT framework. Blockchain, the foundational technology behind Bitcoin, has garnered considerable attention since its inception, and its versatility holds the potential to reshape the IoMT framework. It offers transparent, immutable, and decentralized data storage. It can facilitate personalized and secure patient data management, revolutionize traditional healthcare practices, establish robust data-sharing mechanisms, enhance pharmaceutical supply chain management’s efficiency, and enable the traceability of drugs. Integrating IoMT and blockchain technologies holds significant promise for maximizing their advantages within the healthcare sector, ranging from enhanced data security and integrity to streamlined interoperability and transparency. This integration fortifies the robustness of healthcare data management. It facilitates the seamless sharing and traceability of medical information, ultimately improving patient care and heightened trust within the healthcare ecosystem. Therefore, it is imperative to understand these emerging technologies like IoMT and blockchain in the healthcare industry. To understand the substantial impact of blockchain and IoMT in the healthcare industry, a comprehensive literature review has been performed based on the formulated research questions. Several research articles from well-known databases were identified using the inclusion and exclusion criteria. The review investigates the work to enable the amalgamation of IoMT and Blockchain in the health ecosystem. The research highlighted six different blockchain applications in the healthcare industry: data storage, data sharing, clinical trials, drug tracking, supply management, and remote patient monitoring. In addition, some noteworthy research articles published in this domain in recent years are discussed to comprehend the practical application of this concept. Hence, the research gaps and newer health requirements were identified based on the comprehensive literature review. To achieve the stated objectives, a framework, namely, BlockMedHealth, a lightweight decentralized real-time monitoring and prescription management system, is proposed. The framework uses IoMT and Blockchain technology to store EHRs (Electronic Health Records) and monitor real-time patient data received from the sensors. The patient-centric framework uses an off-chain database, which offers a solution that fulfills data integrity, anonymity, and interoperability requirements. The blockchain network connects patients and healthcare professionals. A permissioned blockchain is utilized to implement the proposed architecture since it restricts access to selected individuals. Self-contained encryption–decryption and primitive cryptographic techniques enhance the system’s security. The proposed framework uses IoMT health sensors such as body temperature, pulse rate, SpO2, and EMG (Electromyogram) in a blockchain-based healthcare ecosystem. The proposed BlockMedHealth has been evaluated to determine that it can process and store RPM (Remote Patient Monitoring) data with encouraging results. A time-based authentication mechanism is used to verify the identities of authorized users. This process utilizes the NIK-512 hashing algorithm in conjunction with passwords and registered timestamps, which strengthens the confidentiality of data. Patient information undergoes encryption before transmission within the network. Further, the proposed framework introduces a sensor registration service that the trusted node employs to assign a distinct identity to each sensor connected to a patient. The performance, security, threat analysis, and resilience to potential attacks contribute towards a robust and smart healthcare system using metrics such as latency, throughput, IoT sensor activity, and resource usage. Finally, the proposed BlockMedHealth system, adaptability, latency, robustness, processing time, battery consumption, memory usage, throughput, computation time, degree of attack, and IoT health sensor activity are considered as the performance metrics that are used to evaluate the system.
Description: PhD Thesis
URI: http://hdl.handle.net/10266/6731
Appears in Collections:Doctoral Theses@CSED

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