Sustainable-Security Assessment Through a Multi Perspective Benchmarking Framework

IF 2 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Cmc-computers Materials & Continua Pub Date : 2022-01-01 DOI:10.32604/cmc.2022.024903

Ahmed Saeed Alfakeeh, Abdulmohsen Almalawi, Fawaz Jaber Alsolami, Yoosef B. Abushark, Asif Irshad Khan, Adel Aboud S. Bahaddad, Md. Mottahir Alam, A. Agrawal, Rajeev Kumar, Raees Ahmad Khan

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引用次数: 0

Abstract

: The current cyber-attack environment has put even the most protected systems at risk as the hackers are now modifying technologies to exploit even the tiniest of weaknesses and infiltrate networks. In this situation, it’s critical to design and construct software that is both secure and long-lasting. While security is the most well-defined aspect of health information software systems, it is equally significant to prioritise sustainability because any health information software system will be more effective if it provides both security and sustainability to the customers at the same time. In this league, it is crucial to determine those characteristics in the systems that can help in the accurate assessment of the sustainable-security of the health information software during the development stage. This research work an outline that software practitioners can follow to enhance the sustainable-security of health information software systems.

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基于多视角基准框架的可持续安全评估

当前的网络攻击环境甚至使最受保护的系统处于危险之中，因为黑客现在正在修改技术，以利用哪怕是最微小的弱点并渗透网络。在这种情况下，设计和构建既安全又持久的软件是至关重要的。虽然安全性是卫生信息软件系统最明确的方面，但优先考虑可持续性同样重要，因为任何卫生信息软件系统如果同时向客户提供安全性和可持续性，将会更有效。在这个联盟中，确定系统中的哪些特征有助于在开发阶段准确评估卫生信息软件的可持续安全性是至关重要的。本研究为软件从业者提供了一个可遵循的框架，以增强卫生信息软件系统的可持续安全性。

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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来源期刊

Cmc-computers Materials & Continua 工程技术-材料科学：综合

CiteScore

5.30

自引率

19.40%

发文量

345

审稿时长

1 months

期刊介绍： This journal publishes original research papers in the areas of computer networks, artificial intelligence, big data management, software engineering, multimedia, cyber security, internet of things, materials genome, integrated materials science, data analysis, modeling, and engineering of designing and manufacturing of modern functional and multifunctional materials. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.