relation: https://khub.utp.edu.my/scholars/8370/
title: Healthcare data privacy measures to cure & care cloud uncertainties
creator: Singh, N.
creator: Jangra, A.
creator: Elamvazuthi, I.
creator: Kashyap, K.
description: Information technology has great potential to improve healthcare quality and efficiency, and thus, has been a major focus of recent healthcare reform efforts. Today, data are usually tackled by leveraging existing encryption cryptographic methods, such that only outsourced data are encrypted and is inaccessible by cloud servers that enables to protect the confidentiality of the data. In this paper, various healthcare data privacy measures are studied and analyzed. It divides the measures on the basis of three major platforms, i.e., Architectural Measures, Technique-based Measures and Algorithmic Measures. Here, a detailed view of wide variety of proposals are beaded together to help researchers to get the best out of all traditional and conventional healthcare data privacy preserving schemes. A comprehensive comparison of the privacy-preserving approaches from the angle of the privacy-preserving requirements' satisfaction is presented. © 2017 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2017
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Singh, N. and Jangra, A. and Elamvazuthi, I. and Kashyap, K.  (2017) Healthcare data privacy measures to cure & care cloud uncertainties.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045838865&doi=10.1109%2fISPCC.2017.8269712&partnerID=40&md5=f659ea6fde510a7e316ae2b8e7c102fa
relation: 10.1109/ISPCC.2017.8269712
identifier: 10.1109/ISPCC.2017.8269712