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      Blockchain-Enabled Security Solutions for Medical Device Integrity and Provenance in Cloud Environments

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          Abstract

          The current period of medicine using digital technology for patient care presents a new level of integration of monitoring devices with the cloud computing environment that enables the collection, storage and access to data in ways that were never possible earlier. As the obvious part of this development, it is worth noting that the objective of such innovation is mostly on the integrity of data, provenance and security. Data integrity from as well as security of the Internet connected healthcare devices should be assured in the first place to keep patient safety and protect data privacy along with improve data-based decision-making. The centralized system and crowded nature of the current equipment are susceptible to single point of failure, data breach and potential manipulations of data, which raise questions and create doubts with regards data management processes pertaining to medical device systems. This work is addressed to the analysis of a novel security system based on blockchain that guarantees the implementation of a high performance with the solution of two medical device integrity and provenance safety issues in the cloud ecosystem. Fundamentally differentiating from the centralized systems that exist today, blockchain technology that is based on distributed database architectures, immutable logs, and consensus mechanisms provides for a new way to bring reliability and traceability to the entire medical device data chain. The suggested procedure is based on properties of blockchain technology. Such a solution can help to provide a clear and secure audit trail for medical devices. Storing, securing and accessing the device data can be carried out credibly, maintaining these data’s integrity and provenance. Ultimately, the solution, rely on the implementation of smart contracts, cryptocurrency processes, and the confidentiality and privacy of data, can be the answer which make up the practice of secure data sharing, data accessing and complying with regulations. The journal creates a modular system combining Medical devices, a cloud platform, and Blockchain solution. The architecture is intended to display the blockchain network's essential components, data validation and access control, and secure data storage mechanisms. Furthermore, the recommended solution implies state-of- the-art security tools, such as data encryption, access control, and abidance by regulatory systems, including HIPAA and GDPR. Implementation of an actual scenario of the proof-of-concept and performance evaluation are done to show the efficiency and performance of the blockchain-based solution provided. The results suggest that the proposed solution can establish the data reliability level, record all the various versions of modifications, and strengthen the security and transparency of medical device data processing in cloud computing. Through the exploration of the applications of blockchain for medical data management that this study proposes, we are laying the foundations of a future healthcare environment, which is expected to be more secure and trustworthy, where the sensor data of medical devices can be reliably controlled and accessed without jeopardizing the patient's safety or data privacy. To a great extent, the suggested solution can contribute to building trust in the digital tools utilized in health care, leading to more well-informed clinical decisions and ultimately improving the patients' results.

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          Most cited references24

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          Where Is Current Research on Blockchain Technology?—A Systematic Review

          Blockchain is a decentralized transaction and data management technology developed first for Bitcoin cryptocurrency. The interest in Blockchain technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain technology from the technical perspective. We have extracted 41 primary papers from scientific databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.
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            An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends

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              Using Convolutional Neural Network to Design and Predict the Forces and Kinematic Performance and External Rotation Moment of the Hip Joint in the Pelvis

              In order to improve the dynamic and kinematic adaptability of the hip joint, this paper presented a control attitude and kinematics and torque of the hip joint with power based neural network control. The CNN neural network uses input data only from the limb designed by the medical software, and is trained by different natural and artificially altered step patterns of healthy individuals. This type of network has been used for deep learning to realize adaptive speed control, dynamic and motion attitude, as well as prediction of force and torque performance. Detailed movement and torque tests were performed using MIMICS and ANATOMY AND PHYSIOLOGY software, and the obtained data were checked and varied by a healthy person, and finally, the test results showed that the neural network control system was able to control the selection. It has a variable and high speed with proper adaptation in various conditions. Finally, MATLAB software was used to design and predict the data of the problem, and favorable results were obtained.
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                Author and article information

                Journal
                International Journal of Innovative Science and Research Technology (IJISRT)
                International Journal of Innovative Science and Research Technology (IJISRT)
                International Journal of Innovative Science and Research Technology
                2456-2165
                April 16 2024
                : 123-135
                Article
                10.38124/ijisrt/IJISRT24APR225
                44e85638-2bb8-48b2-8b4c-1174dca99922
                © 2024
                History

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