DEVELOPMENT OF NETWORK ATTACK MODELING METHOD BASED ON NEURAL NETWORKS AND PROBABILISTIC GRAPHS
In this paper, we proposed new formal model for network attack representation based on artificial neural networks and automata with probabilistic transition functions. A theoretical justification of the proposed method is given in terms of graph theory. The proposed method allows simulating network attacks in real computer systems.