Analytical modeling and assessment of cyber resilience on the base of stochastic networks conversion

In the paper the term cyber resilience is interpreted as the stability of computer networks or systems operating under impact of cyber attacks and other negative impacts, including influence of inappropriate, dubious and harmful information. We consider an approach for construction of analytical models of cyber attacks and negative impacts based on the stochastic networks conversion. This approach has high accuracy and stability of the decisions and has worked well for modeling multi-stage stochastic processes of different nature. The result of the modeling is the distribution function of the time and the average time for implementation of cyber attacks. We also build analytical models for implementation of countermeasures, and integrate them with the analytical models of cyber. As the result the integrated analytical model of the behavior of computer networks under conditions of cyber actions is formed. They allow one to estimate and to choose the most effective countermeasures. These estimates are then used to find the indicators of cyber resilience. The results of experimental evaluation of cyber resilience of computer networks and discussion are given.