A Fuzzy Analytic Network Process for Security Risk Assessment of Web based Hospital Management System
Nawaf Rasheed Alharbe

Nawaf Rasheed Alharbe, Department of Computer Science and Information, Community College, Badr, Taibah University, KSA.
Manuscript received on October 11, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 691-695 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4593119119/2019©BEIESP | DOI: 10.35940/ijitee.A4593.119119
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Software applications have revolutionized human lives. As healthcare industry becomes digitalized, more and more hospitals are now dependent on effective and user-friendly software applications for efficacious management. However, this progressive increase in the use of software applications has led to several security issues. Security risk has probably become the biggest and most sensitive concern in this era for hospital management systems. Assessment of security risk may help in acquiring the level of security that the end user wants. Security assessment needs identification and prioritization of its attributes for publishing guidelines to maintain that level, as security risk is a multidimensional problem. This study has used the Fuzzy ANP methodology to solve this multi criteria based problem. This work also emphasizes on increasing security by assessing the security risk in hospital management system. A real time case study of hospital management system has also been used for validating the results. The acquired results will help in mapping the guidelines and developing new mechanism as per the high prioritized attributes of security risk.
Keywords: Security Risk; Web Applications; Fuzzy Logic; Analytic Network Process.
Scope of the Article: Fuzzy Logic