دورية أكاديمية

Study on Differential Privacy Protection for Medical Set-Valued Data

التفاصيل البيبلوغرافية
العنوان: Study on Differential Privacy Protection for Medical Set-Valued Data
المؤلفون: WANG Mei-shan, YAO Lan, GAO Fu-xiang, XU Jun-can
المصدر: Jisuanji kexue, Vol 49, Iss 4, Pp 362-368 (2022)
بيانات النشر: Editorial office of Computer Science, 2022.
سنة النشر: 2022
المجموعة: LCC:Computer software
LCC:Technology (General)
مصطلحات موضوعية: set-valued data, medical big data, differential privacy, privacy protection, data utility, Computer software, QA76.75-76.765, Technology (General), T1-995
الوصف: Electronic medical data surges along with the constant development of information technologies and medical care digitalization.It provides foundations for further application on data analysis, data mining and intelligent diagnosis.The fact that me-dical data are massive and involve a lot of patient privacy.How to protect patient privacy while using medical data is challenging.The predominant principle for the solutions is anonymity.It is not competent in confidentiality or availability when attackers possess strong background knowledge.This paper proposes an optimized classification tree and an improved Diffpart.In our design, association of data is introduced to sift set-valued data for DP based perturbation, which satisfies the utility and supports statistic query.Then test is conducted with 240000 practical medical data and the results show that the proposed algorithm holds DP distribution and outperforms Diffpart in privacy and utility.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: Chinese
تدمد: 1002-137X
العلاقة: https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-4-362.pdfTest; https://doaj.org/toc/1002-137XTest
DOI: 10.11896/jsjkx.210300032
الوصول الحر: https://doaj.org/article/24cef555bc97433782c8b11d9f54dc12Test
رقم الانضمام: edsdoj.24cef555bc97433782c8b11d9f54dc12
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:1002137X
DOI:10.11896/jsjkx.210300032