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面向医疗物联网自适应多因素认证的数据分类法。

A Data Taxonomy for Adaptive Multifactor Authentication in the Internet of Health Care Things.

机构信息

School of Science, Edith Cowan University, Perth, Australia.

出版信息

J Med Internet Res. 2023 Aug 29;25:e44114. doi: 10.2196/44114.

Abstract

The health care industry has faced various challenges over the past decade as we move toward a digital future where services and data are available on demand. The systems of interconnected devices, users, data, and working environments are referred to as the Internet of Health Care Things (IoHT). IoHT devices have emerged in the past decade as cost-effective solutions with large scalability capabilities to address the constraints on limited resources. These devices cater to the need for remote health care services outside of physical interactions. However, IoHT security is often overlooked because the devices are quickly deployed and configured as solutions to meet the demands of a heavily saturated industry. During the COVID-19 pandemic, studies have shown that cybercriminals are exploiting the health care industry, and data breaches are targeting user credentials through authentication vulnerabilities. Poor password use and management and the lack of multifactor authentication security posture within IoHT cause a loss of millions according to the IBM reports. Therefore, it is important that health care authentication security moves toward adaptive multifactor authentication (AMFA) to replace the traditional approaches to authentication. We identified a lack of taxonomy for data models that particularly focus on IoHT data architecture to improve the feasibility of AMFA. This viewpoint focuses on identifying key cybersecurity challenges in a theoretical framework for a data model that summarizes the main components of IoHT data. The data are to be used in modalities that are suited for health care users in modern IoHT environments and in response to the COVID-19 pandemic. To establish the data taxonomy, a review of recent IoHT papers was conducted to discuss the related work in IoHT data management and use in next-generation authentication systems. Reports, journal articles, conferences, and white papers were reviewed for IoHT authentication data technologies in relation to the problem statement of remote authentication and user management systems. Only publications written in English from the last decade were included (2012-2022) to identify key issues within the current health care practices and their management of IoHT devices. We discuss the components of the IoHT architecture from the perspective of data management and sensitivity to ensure privacy for all users. The data model addresses the security requirements of IoHT users, environments, and devices toward the automation of AMFA in health care. We found that in health care authentication, the significant threats occurring were related to data breaches owing to weak security options and poor user configuration of IoHT devices. The security requirements of IoHT data architecture and identified impactful methods of cybersecurity for health care devices, data, and their respective attacks are discussed. Data taxonomy provides better understanding, solutions, and improvements of user authentication in remote working environments for security features.

摘要

在迈向数字化未来的过程中,医疗保健行业在过去十年中面临着各种挑战,在这个未来中,服务和数据可以随时随地按需获取。互联设备、用户、数据和工作环境的系统被称为医疗物联网(IoHT)。在过去的十年中,IoHT 设备作为具有成本效益的解决方案出现,具有大规模可扩展性,可解决资源有限的约束问题。这些设备满足了远程医疗服务对物理交互之外的需求。然而,IoHT 安全性经常被忽视,因为这些设备是作为解决方案快速部署和配置的,以满足高度饱和行业的需求。在 COVID-19 大流行期间,研究表明网络犯罪分子正在利用医疗保健行业,数据泄露通过身份验证漏洞针对用户凭据。IBM 的报告显示,不良的密码使用和管理以及 IoHT 中缺乏多因素身份验证安全措施会导致数百万美元的损失。因此,医疗保健身份验证安全性转向自适应多因素身份验证(AMFA)以取代传统身份验证方法非常重要。我们发现,缺乏特别关注 IoHT 数据体系结构的数据模型分类法,以提高 AMFA 的可行性。该观点侧重于在数据模型的理论框架中确定关键的网络安全挑战,该框架总结了 IoHT 数据的主要组成部分。这些数据将用于适合现代 IoHT 环境中医疗保健用户的模式,并针对 COVID-19 大流行做出响应。为了建立数据分类法,对最近的 IoHT 论文进行了审查,以讨论下一代身份验证系统中与远程身份验证和用户管理系统相关的 IoHT 数据管理和使用的相关工作。报告、期刊文章、会议和白皮书都针对与远程身份验证和用户管理系统的问题陈述有关的 IoHT 身份验证数据技术进行了审查。仅包含过去十年(2012-2022 年)用英语撰写的出版物,以确定当前医疗保健实践及其对 IoHT 设备的管理中的关键问题。我们从数据管理和对所有用户隐私的敏感性的角度讨论了 IoHT 架构的组件。数据模型解决了 IoHT 用户、环境和设备的安全要求,以实现医疗保健中的 AMFA 自动化。我们发现,在医疗保健身份验证中,由于安全选项较弱和 IoHT 设备的用户配置不佳,发生的重大威胁与数据泄露有关。讨论了 IoHT 数据体系结构的安全要求和针对医疗保健设备、数据及其各自攻击的有影响力的网络安全方法。数据分类法为安全功能提供了对远程工作环境中用户身份验证的更好理解、解决方案和改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56d4/10498322/4b8b3546ec88/jmir_v25i1e44114_fig1.jpg

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