Background As the COVID-19 crisis endures and the virus continues to spread globally, the need for collecting epidemiological data and patient information also grows exponentially. The race against the clock to find a cure and a vaccine to the disease means researchers require storage of increasingly large and diverse types of information; for doctors following patients, recording symptoms and reactions to treatments, the need for storage flexibility is only surpassed by the necessity of storage security. The volume, variety, and variability of COVID-19 patient data requires storage in NoSQL database management systems (DBMSs). But with a multitude of existing NoSQL DBMSs, there is no straightforward way for institutions to select the most appropriate. And more importantly, they suffer from security flaws that would render them inappropriate for the storage of confidential patient data. Motivation This paper develops an innovative solution to remedy the aforementioned shortcomings. COVID-19 patients, as well as medical professionals, could be subjected to privacy-related risks, from abuse of their data to community bullying regarding their medical condition. Thus, in addition to being appropriately stored and analyzed, their data must imperatively be highly protected against misuse. Methods This paper begins by explaining the five most popular categories of NoSQL databases. It also introduces the most popular NoSQL DBMS types related to each one of them. Moreover, this paper presents a comparative study of the different types of NoSQL DBMS, according to their strengths and weaknesses. This paper then introduces an algorithm that would assist hospitals, and medical and scientific authorities to choose the most appropriate type for storing patients’ information. This paper subsequently presents a set of functions, based on web services, offering a set of endpoints that include authentication, authorization, auditing, and encryption of information. These functions are powerful and effective, making them appropriate to store all the sensitive data related to patients. Results and Contributions This paper presents an algorithm to select the most convenient NoSQL DBMS for COVID-19 patients, medical staff, and organizations data. In addition, the paper proposes innovative security solutions that eliminate the barriers to utilizing NoSQL DBMSs to store patients’ data. The proposed solutions resolve several security problems including authentication, authorization, auditing, and encryption. After implementing these security solutions, the use of NoSQL DBMSs will become a much more appropriate, safer, and affordable solution to storing and analyzing patients’ data, which would contribute greatly to the medical and research effort against COVID-19. This solution can be implemented for all types of NoSQL DBMSs; implementing it would result in highly securing patients’ data, and protecting them from any downsides related to data leakage.

中文翻译：

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COVID-19 时期的数据：为医疗数据选择和保护 NoSQL DBMS 的通用方法

背景随着 COVID-19 危机的持续和病毒继续在全球传播，收集流行病学数据和患者信息的需求也呈指数增长。与时间赛跑以寻找治疗该疾病的方法和疫苗意味着研究人员需要存储越来越多、种类越来越多的信息；对于跟踪患者、记录症状和对治疗的反应的医生来说，存储灵活性的需求仅次于存储安全的必要性。COVID-19 患者数据的数量、种类和可变性需要存储在 NoSQL 数据库管理系统 (DBMS) 中。但是，由于现有的 NoSQL DBMS 众多，因此机构没有直接的方法来选择最合适的。更重要的是，它们存在安全漏洞，导致它们不适合存储机密的患者数据。动机 本文开发了一种创新的解决方案来弥补上述缺点。COVID-19 患者以及医疗专业人员可能会面临与隐私相关的风险，从滥用他们的数据到社区欺凌他们的健康状况。因此，除了被适当地存储和分析之外，他们的数据必须受到高度保护以防止滥用。方法 本文首先解释了五种最流行的 NoSQL 数据库类别。它还介绍了与每种类型相关的最流行的 NoSQL DBMS 类型。此外，本文根据其优缺点对不同类型的 NoSQL DBMS 进行了比较研究。然后，本文介绍了一种算法，该算法将帮助医院、医疗和科学机构选择最合适的类型来存储患者信息。本文随后介绍了一组基于 Web 服务的功能，提供一组端点，包括身份验证、授权、审计和信息加密。这些功能强大而有效，适合存储与患者相关的所有敏感数据。结果和贡献 本文提出了一种算法，可以为 COVID-19 患者、医务人员和组织数据选择最方便的 No​​SQL DBMS。此外，本文提出了创新的安全解决方案，消除了使用 NoSQL DBMS 存储患者数据的障碍。提议的解决方案解决了几个安全问题，包括身份验证、授权、审计和加密。在实施这些安全解决方案后，NoSQL DBMS 的使用将成为存储和分析患者数据的更合适、更安全、更实惠的解决方案，这将极大地促进针对 COVID-19 的医疗和研究工作。该解决方案适用于所有类型的 NoSQL DBMS；实施它将导致高度保护患者的数据，并保护他们免受与数据泄漏相关的任何不利影响。这将大大有助于针对 COVID-19 的医学和研究工作。该解决方案适用于所有类型的 NoSQL DBMS；实施它将导致高度保护患者的数据，并保护他们免受与数据泄漏相关的任何不利影响。这将大大有助于针对 COVID-19 的医学和研究工作。该解决方案适用于所有类型的 NoSQL DBMS；实施它将导致高度保护患者的数据，并保护他们免受与数据泄漏相关的任何不利影响。