Algorithmization of processes for detecting vulnerabilities of UMV interfaces based on probabilistic automata

The algorithmic approach based on the methods of adaptive intelligent technology for monitoring the state of objects of computer systems is considered. The approach is focused on the detection of changes in the state of controlled unmanned vehicle resources: communication channel, processor, memory. An adaptive model using the Bayesian classifier for assessing changes in the state of unmanned vehicle resources is presented. The model is based on a probabilistic automaton with adaptive self-tuning. The approach proposed in the article is focused on solving problems of detecting moments in time of changes in the state of controlled unmanned vehicle objects, which are resources: communication channel, processor, memory.