Multi-Level Privacy-Preserving Access Control as a Service for Personal Healthcare Monitoring

Usama Salama, Lina Yao, Xianzhi Wang, Hye-young Paik, A. Beheshti
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引用次数: 18

Abstract

The Internet of Things (IoT) changes many sectors of our lives. In the healthcare domain, IoT presents as mobile medical applications over various sensors that update healthcare professionals on patients' health information. However, IoT-based healthcare systems also face major challenges in protecting patients' privacy via an effective access control system. This paper presents an ambient home solution framework for privacy-preserving monitoring of patients' health status. We focus on two major points: 1) how to use the data collected from ambient and biometric sensors, to perform the high-level task of activity recognition, and 2) how to secure the collected healthcare data via effective access control. We achieve multi-level access control by using Public Key Infrastructure (PKI) for authentication and Attribute-Based Access Control (ABAC) for authorisation. Our access control system regulates access to healthcare data by classification over healthcare professionals and data. Our system provides guidelines to define data classes and healthcare professional groups and specifies security policies to control access to the data classes. The system is flexible and can incorporate more policy rules, professionals, and data classes.
多级隐私保护访问控制作为一种个人健康监测服务
物联网(IoT)改变了我们生活的许多方面。在医疗保健领域,物联网以移动医疗应用的形式出现,通过各种传感器向医疗保健专业人员更新患者的健康信息。然而,基于物联网的医疗保健系统在通过有效的访问控制系统保护患者隐私方面也面临着重大挑战。本文提出了一种环境家庭解决方案框架,用于保护隐私的患者健康状况监测。我们主要关注两个要点:1)如何使用从环境和生物识别传感器收集的数据来执行活动识别的高级任务,以及2)如何通过有效的访问控制来保护收集的医疗保健数据。我们通过使用公钥基础设施(PKI)进行身份验证和使用基于属性的访问控制(ABAC)进行授权来实现多级访问控制。我们的访问控制系统通过对医疗保健专业人员和数据的分类来规范对医疗保健数据的访问。我们的系统提供了定义数据类和医疗保健专业人员组的指导方针,并指定了控制对数据类访问的安全策略。该系统非常灵活,可以包含更多的策略规则、专业人员和数据类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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