ДОСЛІДЖЕННЯ ФУНКЦІЇ ІНТЕНСИВНОСТІ КІБЕРАТАК ЗА ДОПОМОГОЮ СТЕПЕНЕВОГО Р-ПЕРЕТВОРЕННЯ АНАЛІТИЧНОЇ ФУНКЦІЇ

Abstract

Strengthening cybersecurity requires identifying the subjects of the threat, their goals, intentions of attacks on the infrastructure and weaknesses of the information security of the enterprise. To achieve these goals, enterprises need new information security solutions that extend to areas that are protected by traditional security. The levels of evolution and adaptability of viruses, as well as cybersecurity protection policies, respectively, are presented. It is shown that errors in predicting the functions of the intensity of cyberattacks at an enterprise are partially due to the selection of a model in the study of indicators of cyberattacks. Known methodologies for analyzing the intensity of cyberattacks at an enterprise are presented. It is proved that the problems of studying the intensity of cyberattacks and their predictions have been little studied in the scientific literature, which is associated with the unpredictability of cyberattacks and the absence in many cases of real data, as well as available methods for predicting them. Mathematical modeling of time series of the intensity of cyberattacks per enterprise is presented to provide comprehensive solutions and predictions of strengthening the enterprise's resistance against current targeted cyber threats. We consider a first-order nonlinear differential equation, the Bernoulli equation, which describes the process of the time series of the intensity of cyberattacks. The analysis of the intensity function of cyberattacks is carried out analytically due to the power-law p-transformation by the analytical function. Statistical data on the number of cyberattacks at the enterprise are considered, provided that a scheduled audit is carried out once a quarter. The types of cyberattacks to defeat network infrastructure, proprietary applications, the level of patches and server configurations, standard software, and their number at the enterprise for certain time periods are presented. A geometric visualization of the change in the steepness of the logistic curve of the intensity of cyberattacks is presented at various parameter values with a uniform step for the period between scheduled audits when applying p-conversion.