Work place: Sana'a University/ Mareb Branch, Department of Com. Scince, Mareb, 764, Yemen
E-mail: alkhulaidi@mail.ru
Website:
Research Interests: Computer systems and computational processes, Systems Architecture, Distributed Computing, Parallel Computing, Information Systems, Programming Language Theory
Biography
Abdualmajed. A. Alkhulaidi is currently pursuing Ph.D. and currently working as Assistant Professor of software engineering in computer science department, college of education, arts and science (Marib branch), Sana'a University, Yemen. He has published more than 30 research papers in reputed international journals and conferences. His main research work focuses on Software Eng., Distributed Systems, Mobile Programming, Parallel programming and System Analysis.
By Adel A. Nasser Abdualmajed A. Al-Khulaidi Mijahed N. Aljober
DOI: https://doi.org/10.5815/ijitcs.2018.04.02, Pub. Date: 8 Apr. 2018
Generally, measuring the Information Security maturity(ISM) is the first step to build a new knowledge information security management system in an organization. Knowing the ISM level helps organizations decide the type of protection strategies and policies will be taken and their priorities to strengthen their competitive ability. One of the possible ways to solve the problem is a using multiple criteria decision-making (MCDM) methodology. Analytic hierarchy process (AHP) is one of the most commonly used MCDM methods, which combines subjective and personal preferences in the information security assessment process. However, the AHP involves human subjectivity, which introduces vagueness type of uncertainty and requires the use of decision-making under those uncertainties. In this paper, the IS maturity is based on hierarchical multilevel information security gap analysis model for ISO 27001:2013 security standard. The concept of fuzzy set is applied to Analytic Hierarchical Process (AHP) to propose a model for measuring organizations IS maturity under uncertain environment. Using fuzzy AHP approach helps determine more efficiently importance weights of factors and indicators, especially deal with imprecise and uncertain expert comparison judgments. A case study is used to illustrate the better new method for IS evaluation.
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