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IoT and Big Data Technologies for Health Care. Third EAI International Conference, IoTCare 2022, Virtual Event, December 12-13, 2022, Proceedings

Research Article

Research on Medical Sensitive Data Protection Algorithm Based on Differential Privacy

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BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-33545-7_6,
        author={Xiaofeng Li and Zhongwei Chen and Zhichang Huang},
        title={Research on Medical Sensitive Data Protection Algorithm Based on Differential Privacy},
        proceedings={IoT and Big Data Technologies for Health Care. Third EAI International Conference, IoTCare 2022, Virtual Event, December 12-13, 2022, Proceedings},
        proceedings_a={IOTCARE},
        year={2023},
        month={5},
        keywords={Differential Privacy Medical Sensitive Data Data Protection Query Control Model Safety Trust Index R-Tree Clustering Structure},
        doi={10.1007/978-3-031-33545-7_6}
    }
    
  • Xiaofeng Li
    Zhongwei Chen
    Zhichang Huang
    Year: 2023
    Research on Medical Sensitive Data Protection Algorithm Based on Differential Privacy
    IOTCARE
    Springer
    DOI: 10.1007/978-3-031-33545-7_6
Xiaofeng Li1, Zhongwei Chen1,*, Zhichang Huang2
  • 1: College of Information Engineering, Guangxi University of Foreign Languages
  • 2: Information Engineering College, Nanning University
*Contact email: top00112233@163.com

Abstract

In order to avoid the wrong transmission behavior of medical data and realize the effective protection of sensitive information samples, the protection algorithm of medical sensitive data based on differential privacy is studied. According to the application principles of Laplace mechanism and index mechanism, a query control model is constructed, and then the analysis of differential privacy protection technology for medical sensitive data is realized by solving the security trust index. Based on the R-tree clustering structure, according to the sensitivity index calculation results, the search and processing of sensitive objects are completed, and the design of medical sensitive data protection algorithm based on differential privacy is completed. The experimental results show that under the effect of the principle of differential privacy, the error transmission probability of medical sensitive data will never be higher than 10%. It has strong application feasibility in solving the problem of medical data error transmission and effectively protecting sensitive information samples.

Keywords
Differential Privacy Medical Sensitive Data Data Protection Query Control Model Safety Trust Index R-Tree Clustering Structure
Published
2023-05-24
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-33545-7_6
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