Privacy Preserving k-Nearest Neighbor for Medical Diagnosis in e-Health Cloud
المؤلفون المشاركون
المصدر
Journal of Healthcare Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-10-15
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Cloud computing is highly suitable for medical diagnosis in e-health services where strong computing ability is required.
However, in spite of the huge benefits of adopting the cloud computing, the medical diagnosis field is not yet ready to adopt the cloud computing because it contains sensitive data and hence using the cloud computing might cause a great concern in privacy infringement.
For instance, a compromised e-health cloud server might expose the medical dataset outsourced from multiple medical data owners or infringe on the privacy of a patient inquirer by leaking his/her symptom or diagnosis result.
In this paper, we propose a medical diagnosis system using e-health cloud servers in a privacy preserving manner when medical datasets are owned by multiple data owners.
The proposed system is the first one that achieves the privacy of medical dataset, symptoms, and diagnosis results and hides the data access pattern even from e-health cloud servers performing computations using the data while it is still robust against collusion of the entities.
As a building block of the proposed diagnosis system, we design a novel privacy preserving protocol for finding the k data with the highest similarity (PE-FTK) to a given symptom.
The protocol reduces the average running time by 35% compared to that of a previous work in the literature.
Moreover, the result of the previous work is probabilistic, i.e., the result can contain some error, while the result of our PE-FTK is deterministic, i.e., the result is correct without any error probability.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Park, Jeongsu& Lee, Dong Hoon. 2018. Privacy Preserving k-Nearest Neighbor for Medical Diagnosis in e-Health Cloud. Journal of Healthcare Engineering،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1187236
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Park, Jeongsu& Lee, Dong Hoon. Privacy Preserving k-Nearest Neighbor for Medical Diagnosis in e-Health Cloud. Journal of Healthcare Engineering No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1187236
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Park, Jeongsu& Lee, Dong Hoon. Privacy Preserving k-Nearest Neighbor for Medical Diagnosis in e-Health Cloud. Journal of Healthcare Engineering. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1187236
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1187236
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر