02. Minaev V.A., Sychev M.P., Vaits E.V., Bondar K.M. System-Dynamics Modeling of Network Information Operations

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DOI: 10.15507/2658-4123.029.201901.020-039

System-Dynamic Modeling of Network Information Operations

Vladimir A. Minaev
Professor, Department of Information Security, Chair of Information Protection, Bauman Moscow State Technical University (2nd 5, bd. 1 Baumanskaya St., Moscow 105005, Russia), D.Sc. (Engineering), ResearcherID: B-4420-2016, ORCID: https://orcid.org/0000-0002-5342-0864, This email address is being protected from spambots. You need JavaScript enabled to view it.

Mikhail P. Sychev
Professor, Department of Information Security, Chair of Information Protection, Bauman Moscow State Technical University (2nd 5, bd. 1 Baumanskaya St., Moscow 105005, Russia), D.Sc. (Engineering), ResearcherID: E-1068-2019, ORCID: https://orcid.org/0000-0002-7535-7704, This email address is being protected from spambots. You need JavaScript enabled to view it.

Ekaterina V. Vaits
Associate Professor, Department of Information Security, Chair of Information Protection, Bauman Moscow State Technical University (2nd 5, bd. 1 Baumanskaya St., Moscow 105005, Russia), Ph. D. (Engineering), ResearcherID: D-9164-2019, ORCID: https://orcid.org/0000-0002-4629-6252, This email address is being protected from spambots. You need JavaScript enabled to view it.

Konstantin M. Bondar
Professor, Department of Information and Technical Support of Internal Affairs, Far Eastern Law Institute of the Ministry of Internal Affairs of the Russia (15 Kazarmennyy Pereulok, Khabarovsk 680020, Russia), Ph.D., Associate Professor, ResearcherID: D-9910-2019, ORCID: https://orcid.org/0000-0002-6928-0413, This email address is being protected from spambots. You need JavaScript enabled to view it.

Introduction. Information-technical and information-psychological influences are the main negative factors affecting the information security according to the Information Security Doctrine of the Russian Federation. Therefore, modeling, evaluating and forecasting information influences on social groups and organizing adequate information counteraction are urgent tasks of management.
Materials and Methods. The system-dynamic models of information influences in social networks and groups are considered. Their application for purposes of counteraction to information terrorism and extremism is proved. The description in the form of flowcharts is given. Systems of differential equations are presented. Experiments with models using the advanced simulation platform Anylogic have been carried out.
Results. In a sample of Russian settlements based on the cluster analysis there have been found homogeneous typological groups that differ in the average time of disseminating information in social networks. Based on Gibbs’s Postulate, the system-dynamic model of information influences on students has been successfully tested.
Discussion and Conclusion. The high consistency of simulation results with empirical data (determination coefficients of at least 90 %) is shown. Models allow forecasting the information influence and information counteraction and playing different scenarios for the dynamics of these processes.

Keywords: simulation modeling, terrorism, extremism, information influences, information counteraction, management, social network, topology, typology, cluster analysis

For citation: Minaev V.A., Sychev M.P., Vaits E.V., Bondar K.M. System-Dynamics Modeling of Network Information Operations. Inzhenernyye tekhnologii i sistemy = Engineering Technologies and Systems. 2019; 29(1):20-39. DOI: https://doi.org/10.15507/2658-4123.029.201901.020-039

Contribution of the authors: V. A. Minaev – mathematical description of the models, formulation of the problems, discussion of the results; M. P. Sychev – justification of the simulation platform, formulation of conclusions; E. V. Vaits – simulation experiments, description of the results; K. M. Bondar – literature review, analysis of the research results.

All authors have read and approved the final version of the paper.

Submitted 05.12.2018; revised 21.01.2019; published online 29.03.2019

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