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通过基于模糊决策的方法确保医疗保健信息系统的安全。

Securing healthcare information system through fuzzy based decision-making methodology.

机构信息

Department of Information Technology, College of Computers and Information Technology, 125895Taif University, Taif, Saudi Arabia.

Department of Information Technology, 30080Babasaheb Bhimrao Ambedkar University, Lucknow, India.

出版信息

Health Informatics J. 2022 Oct-Dec;28(4):14604582221135420. doi: 10.1177/14604582221135420.

DOI:10.1177/14604582221135420
PMID:36374584
Abstract

The purpose of the healthcare Information System (HIS) is to replace the conventional method of data gathering and organization in hospitals into a modern method of systematic data collection, maintenance and dissemination. There has been an unprecedented rise in the malware and cyber-attacks on HIS recently. Cyber-attacks have become a major crisis for the healthcare industry. To address this scenario, the present paper conducts a study on the security factors integral to the healthcare information system and conducts the performance analysis of these factors. For this intent, the study has employed the Fuzzy Analytic Hierarchy Process (F.AHP) integrated with Technique Order Preference by Similarity to Ideal Solution (TOPSIS) integrated framework for evaluating the performance of each factor. Thereafter, the factors that play a vital role in healthcare data security breaches have been prioritized as per their security weights. Furthermore, the validity of the results obtained by the stated methodology has been established by conducting the sensitivity analysis and comparison of results with the other methods by using the same data set. Based on results thus obtained, the access control and software security have been identified as the most promising security factors.

摘要

医疗保健信息系统(HIS)的目的是将医院中传统的数据收集和组织方法替换为系统的数据收集、维护和传播的现代方法。最近,HIS 受到恶意软件和网络攻击的数量呈前所未有的上升趋势。网络攻击已经成为医疗行业的一大危机。针对这种情况,本文对医疗信息系统中不可或缺的安全因素进行了研究,并对这些因素的性能进行了分析。为此,该研究采用了模糊层次分析法(F.AHP)与逼近理想解排序法(TOPSIS)相结合的方法,对每个因素的性能进行评估。然后,根据安全权重对导致医疗保健数据泄露的关键因素进行了优先级排序。此外,还通过进行敏感性分析以及使用相同数据集与其他方法进行结果比较,验证了所提出的方法的有效性。基于所得到的结果,确定了访问控制和软件安全是最有前途的安全因素。

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