IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v23y2020i3d10.1007_s10729-019-09490-4.html
   My bibliography  Save this article

A privacy protection method for health care big data management based on risk access control

Author

Listed:
  • Mingyue Shi

    (Yunnan University of Finance and Economics
    Key Laboratory of Service Computing and Safety Management of Yunnan Provincial Universities)

  • Rong Jiang

    (Yunnan University of Finance and Economics
    Key Laboratory of Service Computing and Safety Management of Yunnan Provincial Universities)

  • Xiaohan Hu

    (Yunnan University of Finance and Economics
    Key Laboratory of Service Computing and Safety Management of Yunnan Provincial Universities)

  • Jingwei Shang

    (Yunnan University of Finance and Economics
    Key Laboratory of Service Computing and Safety Management of Yunnan Provincial Universities)

Abstract

With the rapid development of modern information technology, the health care industry is entering a critical stage of intelligence. Faced with the growing health care big data, information security issues are becoming more and more prominent in the management of smart health care, especially the problem of patient privacy leakage is the most serious. Therefore, strengthening the information management of intelligent health care in the era of big data is an important part of the long-term sustainable development of hospitals. This paper first identified the key indicators affecting the privacy disclosure of big data in health management, and then established the risk access control model based on the fuzzy theory, which was used for the management of big data in intelligent medical treatment, and solves the problem of inaccurate experimental results due to the lack of real data when dealing with actual problems. Finally, the model is compared with the results calculated by the fuzzy tool set in Matlab. The results verify that the model is effective in assessing the current safety risks and predicting the range of different risk factors, and the prediction accuracy can reach more than 90%.

Suggested Citation

  • Mingyue Shi & Rong Jiang & Xiaohan Hu & Jingwei Shang, 2020. "A privacy protection method for health care big data management based on risk access control," Health Care Management Science, Springer, vol. 23(3), pages 427-442, September.
  • Handle: RePEc:kap:hcarem:v:23:y:2020:i:3:d:10.1007_s10729-019-09490-4
    DOI: 10.1007/s10729-019-09490-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-019-09490-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10729-019-09490-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sajjad Bahrebar & Frede Blaabjerg & Huai Wang & Navid Vafamand & Mohammad-Hassan Khooban & Sima Rastayesh & Dao Zhou, 2018. "A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application," Energies, MDPI, vol. 11(4), pages 1-16, March.
    2. Harish Garg, 2017. "Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision-making process," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 546-571, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Hassan Khooban & Navid Vafamand & Jalil Boudjadar, 2019. "Tracking Control for Hydrogen Fuel Cell Systems in Zero-Emission Ferry Ships," Complexity, Hindawi, vol. 2019, pages 1-9, November.
    2. Fu-Cheng Wang & Kuang-Ming Lin, 2018. "Impacts of Load Profiles on the Optimization of Power Management of a Green Building Employing Fuel Cells," Energies, MDPI, vol. 12(1), pages 1-16, December.
    3. Zengxian Li & Guiwu Wei & Hui Gao, 2018. "Methods for Multiple Attribute Decision Making with Interval-Valued Pythagorean Fuzzy Information," Mathematics, MDPI, vol. 6(11), pages 1-27, October.
    4. Jie Wang & Guiwu Wei & Hui Gao, 2018. "Approaches to Multiple Attribute Decision Making with Interval-Valued 2-Tuple Linguistic Pythagorean Fuzzy Information," Mathematics, MDPI, vol. 6(10), pages 1-45, October.
    5. Mohamed Derbeli & Oscar Barambones & Jose Antonio Ramos-Hernanz & Lassaad Sbita, 2019. "Real-Time Implementation of a Super Twisting Algorithm for PEM Fuel Cell Power System," Energies, MDPI, vol. 12(9), pages 1-20, April.
    6. Zeeshan Ali & Tahir Mahmood & Gustavo Santos-García, 2021. "Heronian Mean Operators Based on Novel Complex Linear Diophantine Uncertain Linguistic Variables and Their Applications in Multi-Attribute Decision Making," Mathematics, MDPI, vol. 9(21), pages 1-37, October.
    7. Jianping Lu & Tingting He & Guiwu Wei & Jiang Wu & Cun Wei, 2020. "Cumulative Prospect Theory: Performance Evaluation of Government Purchases of Home-Based Elderly-Care Services Using the Pythagorean 2-tuple Linguistic TODIM Method," IJERPH, MDPI, vol. 17(6), pages 1-21, March.
    8. K. Rahman & A. Ali & S. Abdullah & F. Amin, 2018. "Approaches to Multi-Attribute Group Decision Making Based on Induced Interval-Valued Pythagorean Fuzzy Einstein Aggregation Operator," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 343-361, November.
    9. Andrés A. Zúñiga & João F. P. Fernandes & Paulo J. C. Branco, 2023. "Fuzzy-Based Failure Modes, Effects, and Criticality Analysis Applied to Cyber-Power Grids," Energies, MDPI, vol. 16(8), pages 1-34, April.
    10. Mohammed Yousri Silaa & Mohamed Derbeli & Oscar Barambones & Ali Cheknane, 2020. "Design and Implementation of High Order Sliding Mode Control for PEMFC Power System," Energies, MDPI, vol. 13(17), pages 1-15, August.
    11. Gulfam Shahzadi & Muhammad Akram & Ahmad N. Al-Kenani, 2020. "Decision-Making Approach under Pythagorean Fuzzy Yager Weighted Operators," Mathematics, MDPI, vol. 8(1), pages 1-20, January.
    12. Xiumei Deng & Jie Wang & Guiwu Wei & Mao Lu, 2018. "Models for Multiple Attribute Decision Making with Some 2-Tuple Linguistic Pythagorean Fuzzy Hamy Mean Operators," Mathematics, MDPI, vol. 6(11), pages 1-28, October.
    13. Joanna Fabis-Domagala & Mariusz Domagala & Hassan Momeni, 2021. "A Matrix FMEA Analysis of Variable Delivery Vane Pumps," Energies, MDPI, vol. 14(6), pages 1-14, March.
    14. Chen, Guohua & Li, Geliang & Xie, Mulin & Xu, Qiming & Zhang, Geng, 2024. "A probabilistic analysis method based on Noisy-OR gate Bayesian network for hydrogen leakage of proton exchange membrane fuel cell," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    15. Heng Zhang & Yang Yang & Tianyu Liu & Honglong Chang, 2018. "Boosting the Power-Generation Performance of Micro-Sized Al-H 2 O 2 Fuel Cells by Using Silver Nanowires as the Cathode," Energies, MDPI, vol. 11(9), pages 1-10, September.
    16. Zeng, Shouzhen & Zhang, Na & Zhang, Chonghui & Su, Weihua & Carlos, Llopis-Albert, 2022. "Social network multiple-criteria decision-making approach for evaluating unmanned ground delivery vehicles under the Pythagorean fuzzy environment," Technological Forecasting and Social Change, Elsevier, vol. 175(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:hcarem:v:23:y:2020:i:3:d:10.1007_s10729-019-09490-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.