Study of the reliability of the impact of threats on the level of security of the information protection system and the object of critical infrastructure based on the results of cognitive modeling

The rapid development of information technology has led to new challenges and threats to information security. Therefore, it is important to solve the problem of ensuring the proper level of security of systems when exposed to potential threats. Particular attention is paid to the safety of critical infrastructure and information protection systems, violations of the functioning of which can lead to large-scale consequences of a negative nature. In this regard, the study of the reliability of the impact of threats on the level of security of the information protection system and the object of critical infrastructure determined by the script modeling on the basis of cognitive approach has been conducted. At the same time, the multiple regression analysis apparatus is used, which allows to trace the link between threats and the security of the investigated systems, assessing the degree of likely impact. To achieve this goal, based on the researched cognitive models to assess the level of security of information protection systems and the object of critical infrastructure, analytical expressions of linear correlational dependence between the most important concepts of each model separately and the protection of the relevant systems are formed. In order to compare the impact of threats on the security of the information protection system and the object of critical infrastructure, standardized regression coefficients are defined, which show how much values the dependent variable will change on average while increasing only one independent variable and the elasticity ratios by which the average dependent variable will change by one percent. The analysis of the obtained values of these indicators has allowed to confirm the accuracy of the results obtained as a result of script modeling on a cognitive approach

information security; security threats; cognitive modeling; fuzzy cognitive map; multiple regression analysis