基于神经网络的PHRs隐私策略评价与分类

I. Carrión, J. Alemán, Chrisina Jayne, D. Palmer-Brown, J. A. Alvarez, J. M. C. D. Gea
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引用次数: 5

摘要

保健服务提供者对提供可存储个人健康信息的个人健康记录越来越感兴趣。在PHRs中,对数据的访问由患者控制,而不是由医疗保健提供者控制。尽管使用phr可以获得许多好处,但phr也带来了重要的安全和隐私挑战。本文对22个基于web的免费phr的隐私政策进行了综述。我们的目标是衡量采用国际标准和成本对隐私和安全特征的影响。根据ISO/TS 13606-4标准提取安全性和隐私性特征。进行了统计分析,并进行了基于神经网络的PHRs分类。可以对phr的当前隐私政策进行一些改进,以加强对其他用户数据的管理、向用户通知隐私政策更改以及访问审计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation and Neuronal Network-Based Classification of the PHRs Privacy Policies
There has been growing interest by health services providers in providing PHRs (Personal Health Records) which can store individual's personal health information. In PHRs, access to data is controlled by the patient, not by the health care provider. Although a number of benefits can be achieved with the PHRs, important security and privacy challenges of PHRs arise. In this paper a review of the privacy policies of 22 free web-based PHRs is presented. Our objective is to measure the effects of adoption of international standards and cost on privacy and security characteristics. Security and privacy characteristics were extracted according to the standard ISO/TS 13606-4. A statistical analysis was conducted and a neural network-based classification of PHRs was performed. Some improvements can be done to current privacy policies of PHRs to enhance management of other users' data, notification of changes in privacy policy to users and access audits.
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