Information processing on the computer system state using probabilistic automata
Sergey Semyonov, Svitlana Gavrylenko, Viktor Chelak · 2017
The paper deals with the processing of information on the state of a computer system using probabilistic automata. An intelligent system model for the detection and classification of malicious software is proposed which compares a set of features that are characteristic for different classes of viruses with multiple states of the machine. The analysis process is reduced to the modeling of the automaton operation taking into account the probability of transition from state to state where each step is recalculated depending on the environment reaction. The received research results allow one to draw a conclusion about the possibility of using the offered system for harmful software detection.