ORCID
O.M. Akash: https://orcid.org/0009-0002-0140-5117
We'am Adel Talafha: https://orcid.org/0009-0000-9470-5252
Mamdouh Gomaa: https://orcid.org/0009-0000-4426-5965
Article Type
Research Article
Abstract
The choice of artificial intelligence (AI) software for cybersecurity testing is a multi-criteria decision-making approach (MCDM) due to it including different criteria. Evaluation decision making problems include uncertainty and vague information. So, the neutrosophic set is used in this study to overcome this uncertainty and vague information. It has three functions such as truth, indeterminacy, and falsity functions. Type-2 neutrosophic numbers is a type of neutrosophic set that includes nine membership functions. This study uses the average method of computing the criteria weights. The CoCoSo method is used to rank alternatives. Six experts and decision makers created the decision makers using the type-2 neutrosophic numbers. A case study with ten criteria and 15 alternatives is solved in this study. Sensitivity analysis is conducted to show the impact of changing in the parameter on the ranks. The results show the rank of alternatives is stable in different cases. Comparative analysis is conducted in this study. The results show the proposed approach is effective compared to other methods.
Keywords
Type-2 neutrosophic set, Uncertainty, Artificial intelligence, Attacks, CyberSecuity, Testing
How to Cite
Akash, O.M.; Talafha, We’am Adel; and Gomaa, Mamdouh
(2025)
"Type-2 Neutrosophic Numbers for Artificial Intelligence Software Choice for Cybersecurity Testing,"
Neutrosophic Systems with Applications: Vol. 25:
Iss.
7, Article 2.
DOI: https://doi.org/10.63689/2993-7159.1285
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
