Open Access

ARTICLE

Unified Computational Modelling for Healthcare Device Security Assessment

Shakeel Ahmed^*, Abdulaziz Alhumam

Department of Computer Science, College of Computer Sciences and Information Technology King Faisal University, Al-Ahsa, 31982, Kingdom of Saudi Arabia

* Corresponding Author: Shakeel Ahmed. Email:

Computer Systems Science and Engineering 2021, 37(1), 1-18. https://doi.org/10.32604/csse.2021.015775

Received 16 November 2020; Accepted 20 December 2020; Issue published 05 February 2021

Abstract

This article evaluates the security techniques that are used to maintain the healthcare devices, and proposes a mathematical model to list these in the order of priority and preference. To accomplish the stated objective, the article uses the Fuzzy Analytic Network Process (ANP) integrated with Technical for Order Preference by Similarities to Ideal Solution (TOPSIS) to find the suitable alternatives of the security techniques for securing the healthcare devices from trespassing. The methodology is enlisted to rank the alternatives/ techniques based on their weights’ satisfaction degree. Thereafter, the ranks of the alternatives determine the order of priority for the techniques used in healthcare security. The findings of our analysis cite that Machine Learning (ML) based healthcare devices obtained the highest priority among all the other security techniques. Hence the developers, manufacturers and researchers should focus on the ML techniques for securing the healthcare devices. The results drawn through the aid of the suggested mathematical model would be a corroborative reference for the developers and the manufacturers in assessing the security techniques of the healthcare devices.

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Citations