Authors: Kateryna Mokliakova , Tetiana Babenko, Andrii Bigdan, Vira Ignisca
Affiliation: Faculty of Information Technology, Taras Shevchenko National University of Kyiv, Ukraine


Keywords: information security auditor, personnel evaluation, critical infrastructure facilities, Rush model, Binary selection with logistic function, artificial neural networks
ABSTRACT. In this article, we describe an approach to mitigate information security auditors hiring process with usage of different models combination. A method of assessing the professional competencies of information security auditors that work with critical infrastructure facilities based on certification built using Rush models and Binary selection of personnel using the logistics function, and automated with artificial network application


1. Cabinet of Ministers of Ukraine, “Regulations on the Administration of the State Service for Special Communications and Information Protection of Ukraine”, Normative document, [Online]. Available:
2. ISO/IEC 19011, Normative document, 2018, [Online]. Available:
3. ZINCHENKO A. A., Modeling of processes of selection and assessment of personnel - Moscow, 2016 [Online]. Available:
4. ISACA: organization [Online]. Available:
5. The Institute for internal auditors [Online]. Available:
6. ISO 27000 standards family [Online]. Available:
7. Payment Card Industry Data Security Standard (PCI DSS) [Online]. Available:
8. Carlo Magno, Demonstrating the Difference between Classical Test Theory and Item Response Theory Using Derived Test Data 2009 at The International Journal of Educational and Psychological Assessment [Online]. Available:
9. Item Response Theory [Online]. Available:
10. DEMENCHENKO O.G. Mathematical foundations of Rasch Measurement // Pedagogical Measurements, №1, 2010
11. GREENE W. H. Econometric Analysis / W. H. Greene. – New Jersey : Prentice Hall, 2012. – 802 p
12. IZENMAN A. J. Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning Springer / A.J. Izenman. – New York: Springer-Verlag, 2008. – 760 p.
13. Kamynin L.I. Mathematical analysis. T. 1, 2. – 2001, [Online]. Available:
14. V.V. Kruglov, V.V. Borisov Artificial neural networks. Theory and practice, 2002, [Online]. Available:
15. Snehashish Chakravert, Deepti Moyi Sahoo, Nisha Rani Mahato: McCulloch-Pitts Neuron model, 2019 , [Online]. Available:
16. Yasnitsky L.N. Introduction to artificial intelligence, 2005, [Online]. Available:
17. Terekhov V.A., Efimov D.V., Tyukin I.Yu.: Neural network control systems, 2002, [Online]. Available:
18. Daniel McFadden: Conditional logit analysis of qualitative choice behaviorm, 1973, [Online]. Availabel:
19. Tom Fawcett: An introduction to ROC analysis, 2006 [Online]. Available: