Privacy-preserving self-helped medical diagnosis scheme based on secure two-party computation in wireless sensor networks.

Yi Sun,Qiaoyan Wen,Yudong Zhang,Wenmin Li

doi:10.1155/2014/214841

Abstract

With the continuing growth of wireless sensor networks in pervasive medical care, people pay more and more attention to privacy in medical monitoring, diagnosis, treatment, and patient care. On one hand, we expect the public health institutions to provide us with better service. On the other hand, we would not like to leak our personal health information to them. In order to balance this contradiction, in this paper we design a privacy-preserving self-helped medical diagnosis scheme based on secure two-party computation in wireless sensor networks so that patients can privately diagnose themselves by inputting a health card into a self-helped medical diagnosis ATM to obtain a diagnostic report just like drawing money from a bank ATM without revealing patients' health information and doctors' diagnostic skill. It makes secure self-helped disease diagnosis feasible and greatly benefits patients as well as relieving the heavy pressure of public health institutions.

Highlights

With the rapid development of science, more and more advanced technologies such as the internet of things and cloud computing are utilized in the area of modern medicine and this trend further pushes healthcare into the digital era [1,2,3]
Inspired by daily used bank automated teller machine (ATM), we introduce the privacy-preserving self-helped medical diagnosis ATM (MD-ATM) so that after obtaining a healthcare card that stores some information about the health data which is collected by various sensor medical devices, patients can privately diagnose himself by inserting the health card into the MD-ATM to obtain diagnostic report just like drawing money from a bank ATM without revealing patient’s health information and the disease database or doctors’ diagnostic skill
(ii) We firstly propose the privacy-preserving self-helped MD-ATM to construct a secure medical diagnosis scheme following the idea of secure two-party computation (STC)

Summary

Introduction

With the rapid development of science, more and more advanced technologies such as the internet of things and cloud computing are utilized in the area of modern medicine and this trend further pushes healthcare into the digital era [1,2,3]. Starting from the aspiration of Computational and Mathematical Methods in Medicine the patient, the most secure and plausible diagnostic method is to apply the processed data rather than the original data to interact with the hospital which owns a disease database to diagnose the health status privately. Inspired by daily used bank automated teller machine (ATM), we introduce the privacy-preserving self-helped medical diagnosis ATM (MD-ATM) so that after obtaining a healthcare card that stores some information about the health data which is collected by various sensor medical devices, patients can privately diagnose himself by inserting the health card into the MD-ATM to obtain diagnostic report just like drawing money from a bank ATM without revealing patient’s health information and the disease database or doctors’ diagnostic skill. (ii) We firstly propose the privacy-preserving self-helped MD-ATM to construct a secure medical diagnosis scheme following the idea of STC. We summarize our work of this paper in the last section

Preliminaries

System Model

Our Scheme

Analysis

Conclusions