IEICE TRANSACTIONS on Information
PDPM: A Patient-Defined Data Privacy Management with Nudge Theory in Decentralized E-Health Environments
Summary :
A private decentralized e-health environment, empowered by blockchain technology, grants authorized healthcare entities to legitimately access the patient's medical data without relying on a centralized node. Every activity from authorized entities is recorded immutably in the blockchain transactions. In terms of privacy, the e-health system preserves a default privacy option as an initial state for every patient since the patients may frequently customize their medical data over time for several purposes. Moreover, adjustments in the patient's privacy contexts are often solely from the patient's initiative without any doctor or stakeholders' recommendation. Therefore, we design, implement, and evaluate user-defined data privacy utilizing nudge theory for decentralized e-health systems named PDPM to tackle these issues. Patients can determine the privacy of their medical records to be closed to certain parties. Data privacy management is dynamic, which can be executed on the blockchain via the smart contract feature. Tamper-proof user-defined data privacy can resolve the dispute between the e-health entities related to privacy management and adjustments. In short, the authorized entities cannot deny any changes since every activity is recorded in the ledgers. Meanwhile, the nudge theory technique supports providing the best patient privacy recommendations based on their behaviour activities even though the final decision rests on the patient. Finally, we demonstrate how to use PDPM to realize user-defined data privacy management in decentralized e-health environments.
- Publication
- IEICE TRANSACTIONS on Information Vol.E104-D No.11 pp.1839-1849
- Publication Date
- 2021/11/01
- Publicized
- 2021/08/24
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2021NGP0015
- Type of Manuscript
- Special Section PAPER (Special Section on Next-generation Security Applications and Practice)
- Category
Authors
Seolah JANG
Pukyong National University
Sandi RAHMADIKA
Pukyong National University
Sang Uk SHIN
Pukyong National University
Kyung-Hyune RHEE
Pukyong National University
Keyword
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Seolah JANG, Sandi RAHMADIKA, Sang Uk SHIN, Kyung-Hyune RHEE, "PDPM: A Patient-Defined Data Privacy Management with Nudge Theory in Decentralized E-Health Environments" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 11, pp. 1839-1849, November 2021, doi: 10.1587/transinf.2021NGP0015.
Abstract: A private decentralized e-health environment, empowered by blockchain technology, grants authorized healthcare entities to legitimately access the patient's medical data without relying on a centralized node. Every activity from authorized entities is recorded immutably in the blockchain transactions. In terms of privacy, the e-health system preserves a default privacy option as an initial state for every patient since the patients may frequently customize their medical data over time for several purposes. Moreover, adjustments in the patient's privacy contexts are often solely from the patient's initiative without any doctor or stakeholders' recommendation. Therefore, we design, implement, and evaluate user-defined data privacy utilizing nudge theory for decentralized e-health systems named PDPM to tackle these issues. Patients can determine the privacy of their medical records to be closed to certain parties. Data privacy management is dynamic, which can be executed on the blockchain via the smart contract feature. Tamper-proof user-defined data privacy can resolve the dispute between the e-health entities related to privacy management and adjustments. In short, the authorized entities cannot deny any changes since every activity is recorded in the ledgers. Meanwhile, the nudge theory technique supports providing the best patient privacy recommendations based on their behaviour activities even though the final decision rests on the patient. Finally, we demonstrate how to use PDPM to realize user-defined data privacy management in decentralized e-health environments.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021NGP0015/_p
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@ARTICLE{e104-d_11_1839,
author={Seolah JANG, Sandi RAHMADIKA, Sang Uk SHIN, Kyung-Hyune RHEE, },
journal={IEICE TRANSACTIONS on Information},
title={PDPM: A Patient-Defined Data Privacy Management with Nudge Theory in Decentralized E-Health Environments},
year={2021},
volume={E104-D},
number={11},
pages={1839-1849},
abstract={A private decentralized e-health environment, empowered by blockchain technology, grants authorized healthcare entities to legitimately access the patient's medical data without relying on a centralized node. Every activity from authorized entities is recorded immutably in the blockchain transactions. In terms of privacy, the e-health system preserves a default privacy option as an initial state for every patient since the patients may frequently customize their medical data over time for several purposes. Moreover, adjustments in the patient's privacy contexts are often solely from the patient's initiative without any doctor or stakeholders' recommendation. Therefore, we design, implement, and evaluate user-defined data privacy utilizing nudge theory for decentralized e-health systems named PDPM to tackle these issues. Patients can determine the privacy of their medical records to be closed to certain parties. Data privacy management is dynamic, which can be executed on the blockchain via the smart contract feature. Tamper-proof user-defined data privacy can resolve the dispute between the e-health entities related to privacy management and adjustments. In short, the authorized entities cannot deny any changes since every activity is recorded in the ledgers. Meanwhile, the nudge theory technique supports providing the best patient privacy recommendations based on their behaviour activities even though the final decision rests on the patient. Finally, we demonstrate how to use PDPM to realize user-defined data privacy management in decentralized e-health environments.},
keywords={},
doi={10.1587/transinf.2021NGP0015},
ISSN={1745-1361},
month={November},}
Copy
TY - JOUR
TI - PDPM: A Patient-Defined Data Privacy Management with Nudge Theory in Decentralized E-Health Environments
T2 - IEICE TRANSACTIONS on Information
SP - 1839
EP - 1849
AU - Seolah JANG
AU - Sandi RAHMADIKA
AU - Sang Uk SHIN
AU - Kyung-Hyune RHEE
PY - 2021
DO - 10.1587/transinf.2021NGP0015
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2021
AB - A private decentralized e-health environment, empowered by blockchain technology, grants authorized healthcare entities to legitimately access the patient's medical data without relying on a centralized node. Every activity from authorized entities is recorded immutably in the blockchain transactions. In terms of privacy, the e-health system preserves a default privacy option as an initial state for every patient since the patients may frequently customize their medical data over time for several purposes. Moreover, adjustments in the patient's privacy contexts are often solely from the patient's initiative without any doctor or stakeholders' recommendation. Therefore, we design, implement, and evaluate user-defined data privacy utilizing nudge theory for decentralized e-health systems named PDPM to tackle these issues. Patients can determine the privacy of their medical records to be closed to certain parties. Data privacy management is dynamic, which can be executed on the blockchain via the smart contract feature. Tamper-proof user-defined data privacy can resolve the dispute between the e-health entities related to privacy management and adjustments. In short, the authorized entities cannot deny any changes since every activity is recorded in the ledgers. Meanwhile, the nudge theory technique supports providing the best patient privacy recommendations based on their behaviour activities even though the final decision rests on the patient. Finally, we demonstrate how to use PDPM to realize user-defined data privacy management in decentralized e-health environments.
ER -
English
