Adaptive trainable model for detecting vulnerabilities of UMV interfaces based on probabilistic automates

The purpose of this work is to develop a model that will provide an opportunity to study the processes of detecting vulnerabilities of UMV interfaces in dynamically changing external environment. An algorithmic approach based on adaptive intelligent technology methods for monitoring of the state of UMV resources is considered. An adaptive trainable model using probabilistic estimation of changes in the stateof UMV resources as well as nonparametrical statistics methods are presented.