Biblio

The features of socio-cyber-physical systems are presented, which dictate the need to revise traditional management methods and transform the management system in such a way that it takes into account the presence of a person both in the control object and in the control loop. The use of situational control mechanisms is proposed. The features of this approach and its comparison with existing methods of situational awareness are presented. The comparison has demonstrated wider possibilities and scope for managing socio-cyber-physical systems. It is recommended to consider a wider class of types of relations that exist in socio-cyber-physical systems. It is indicated that such consideration can be based on the use of pseudo-physical logics considered in situational control. It is pointed out that it is necessary to design a classifier of situations (primarily in cyberspace), instead of traditional classifiers of threats and intruders.

Modern cyberattacks are the most powerful disturbance factor for computer networks, as they have a complex and devastating impact. The impact of cyberattacks is primarily aimed at disrupting the performance of computer network protection means. Therefore, managing this defense system in the face of cyberattacks is an important task. The paper examines a technique for constructing an effective control system for a computer network security system operating in real time in the context of cyber attacks. It is supposed that it is built on the basis of constructing a system state space and a stack of control decisions. The probability of finding the security system in certain state at each control step is calculated using a finite Markov chain. The technique makes it possible to predict the number of iterations for managing the security system when exposed to cyber attacks, depending on the segment of the space of its states and the selected number of transitions, as well as automatically generate control decisions. An algorithm has been developed for situational control of a computer network security system in conditions of cyber attacks. The experimental results obtained using the generated dataset demonstrated the high efficiency of the developed technique and the ability to use it to determine the parameters that are most susceptible to abnormal deviations during the impact of cyber attacks.