Security Enhanced Cloud-Based Remote Patient Monitoring System with Human Digital Twin and OPC UA
Trivedi, Jolly (2024-07-31)
Security Enhanced Cloud-Based Remote Patient Monitoring System with Human Digital Twin and OPC UA
(31.07.2024)
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
avoin
Julkaisun pysyvä osoite on:
https://urn.fi/URN:NBN:fi-fe2024080263496
https://urn.fi/URN:NBN:fi-fe2024080263496
Tiivistelmä
The introduction of Human Digital Twin (HDT) technology marks a new era of personalized healthcare, with unparalleled prospects for Remote Patient Monitoring (RPM). This thesis presents a novel architecture for securing patient data and enhancing personalized healthcare in RPM, addressing the critical need for robust cybersecurity measures in RPM systems.
The proposed architecture seamlessly combines healthcare wearable devices with the OPC Unified Architecture (OPC UA) protocol, ensuring secure and interoperable communication. In the proposed architecture, a multi-layered security strategy is implemented by usingusing pseudonymization techniques that safeguard data andreserving its utility for personalized treatment. This pseudonymized data is then transferred to the cloud via Azure IoT Hub, creating a secure pipeline for sensitive health information. The journey culminates in Azure Digital Twin, where advanced analytics and predictive modeling open the doors for truly personalized healthcare.
This design distinguishes itself by adhering to NIST SP 1800-30B criteria. The goal is not only to construct a secure system but also to provide a framework that can adapt to emerging threats. The efficacy of this technique is proved through thorough testing, including a Chi-Square study that compares the proposed RPM to current systems. Testing and statistics reveal the proposed design outperforms existing RPM systems. This study proposes a robust, scalable, and standards-compliant solution to one of healthcare’s most serious issues. It is more than simply an architecture. It is also a road map for the future of secure, personalized remote patient care. To verify the suggested system’s scalability and real-world performance, more investigation and pilot testing are required.
The proposed architecture seamlessly combines healthcare wearable devices with the OPC Unified Architecture (OPC UA) protocol, ensuring secure and interoperable communication. In the proposed architecture, a multi-layered security strategy is implemented by usingusing pseudonymization techniques that safeguard data andreserving its utility for personalized treatment. This pseudonymized data is then transferred to the cloud via Azure IoT Hub, creating a secure pipeline for sensitive health information. The journey culminates in Azure Digital Twin, where advanced analytics and predictive modeling open the doors for truly personalized healthcare.
This design distinguishes itself by adhering to NIST SP 1800-30B criteria. The goal is not only to construct a secure system but also to provide a framework that can adapt to emerging threats. The efficacy of this technique is proved through thorough testing, including a Chi-Square study that compares the proposed RPM to current systems. Testing and statistics reveal the proposed design outperforms existing RPM systems. This study proposes a robust, scalable, and standards-compliant solution to one of healthcare’s most serious issues. It is more than simply an architecture. It is also a road map for the future of secure, personalized remote patient care. To verify the suggested system’s scalability and real-world performance, more investigation and pilot testing are required.