A Cloud Based Solution for Collaborative and Secure Sharing of Medical Data

Author:

Marwan Mbarek1,Kartit Ali1,Ouahmane Hassan2

Affiliation:

1. Chouaib Doukkali University, Morocco

2. LTI Laboratory, ENSA, Chouaib Doukkali University, El Jadida, Morocco

Abstract

Healthcare sector is under pressure to reduce costs while delivering high quality of care services. This situation requires that clinical staff, equipment and IT tools to be used more equitably, judiciously and efficiently. In this sense, collaborative systems have the ability to provide opportunities for healthcare organizations to share resources and create a collaborative working environment. The lack of interoperability between dissimilar systems and operating costs are the major obstacle to the implementation of this concept. Fortunately, cloud computing has great potential for addressing interoperability issues and significantly reducing operating costs. Since the laws and regulations prohibit the disclosure of health information, it is necessary to carry out a comprehensive study on security and privacy issues in cloud computing. Based on their analysis of these constraints, the authors propose a simple and efficient method that enables secure collaboration between healthcare institutions. For this reason, they propose Secure Multi-party Computation (SMC) protocols to ensure compliance with data protection legislation. Specifically, the authors use Paillier scheme to protect medical data against unauthorized usage when outsourcing computations to a public cloud. Another useful feature of this algorithm is the possibility to perform arithmetic operations over encrypted data without access to the original data. In fact, the Paillier algorithm is an efficient homomorphic encryption that supports addition operations on ciphertexts. Based on the simulation results, the proposed framework helps healthcare organizations to successfully evaluate a public function directly on encrypted data without revealing their private inputs. Consequently, the proposed collaborative application ensures privacy of medical data while completing a task.

Publisher

IGI Global

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3