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.

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

The article proposes an approach to ensuring the functioning of Software-Defined Networks (SDN) in cyber attack conditions based on the analytical modeling of cyber attacks using the method of topological transformation of stochastic networks. Unlike other well-known approaches, the proposed approach combines the SDN resilience assessment based on analytical modeling and the SDN state monitoring based on a neural network. The mathematical foundations of this assessment are considered, which make it possible to calculate the resilience indicators of SDN using analytical expressions. As the main indicator, it is proposed to use the correct operation coefficient for the resilience of SDN. The approach under consideration involves the development of verbal models of cyber attacks, followed by the construction of their analytical models. In order to build analytical models of cyber attacks, the method of topological transformation of stochastic networks (TTSN) is used. To obtain initial data in the simulation, the SDN simulation bench was justified and deployed in the EVE-NG (Emulated Virtual Environment Next Generation) virtual environment. The result of the simulation is the time distribution function and the average time for the cyber attack implementation. These results are then used to evaluate the SDN resilience indicators, which are found by using the Markov processes theory. In order to ensure the resilience of the SDN functioning, the article substantiates an algorithm for monitoring the state of controllers and their automatic restructuring, built on the basis of a neural network. When one is choosing a neural network, a comparative evaluation of the convolutional neural network and the LSTM neural network is carried out. The experimental results of analytical modeling and simulation are presented and their comparative evaluation is carried out, which showed that the proposed approach has a sufficiently high accuracy, completeness of the obtained solutions and it took a short time to obtain the result.

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Ensuring SDN Resilience under the Influence of Cyber Attacks: Combining Methods of Topological Transformation of Stochastic Networks, Markov Processes, and Neural Networks

Nowadays, increasing the resilience of information and telecommunication networks in the face of many different threats and impacts is one of the most important areas of network security. The task of optimal structural reservation of the telecommunication network is formulated as a search for a reservation option, which ensures maximum resilience of the network when meeting the cost constraints of the reservation network elements. The paper describes the problem of optimal structural reservation for improving the network resilience. Possible solutions of this problem are considered. It is shown that the preferred method to solve the problem is the method of Lagrange multipliers. Results of experimental evaluation of proposed method are presented.

An Approach for Improving the Network Resilience Based on Optimal Structural Reservation

Nowadays, increasing the resilience of information and telecommunication networks in the face of many different threats and impacts is one of the most important areas of network security. The task of optimal structural reservation of the telecommunication network is formulated as a search for a reservation option, which ensures maximum resilience of the network when meeting the cost constraints of the reservation network elements. The paper describes the problem of optimal structural reservation for improving the network resilience. Possible solutions of this problem are considered. It is shown that the preferred method to solve the problem is the method of Lagrange multipliers. Results of experimental evaluation of proposed method are presented. 

The paper suggests an approach to computer network resilience assessment under exposure of cyber attacks, based on analytical attack modeling using the method of stochastic networks transformations. The network resilience assessment methodology and main stages of the proposed method for analytical modeling of cyber attacks are studied. It is shown how the proposed method can be used to generate the reference analytical model of the computer attack. Experimental evaluation of the proposed method for analytical modeling of attacks and developed methodology for assessing resilience of the network under exposure of cyber attacks showed high adequacy of the obtained results and high efficiency of their calculation.

Mikhail Kocinyak

Papers

Assessment of Computer Network Resilience Under Impact of Cyber Attacks on the Basis of Stochastic Networks Conversion