Problem statement. Unintentional violations by a user of instructions for working with an information system, leading to information security threats (unintentional insider incidents), are a serious issue in the field of information security. The main cause of such violations is that, due to a certain psycho-emotional state of the user, a deviation in behavior occurs, and the user may make mistakes both in choosing and in working with system interface elements: for example, entering confidential data into "open" fields. The aim of this work is to describe a software tool for modeling, developed based on the author's system interface model and instructions. Research methods: computer modeling, software engineering, experiment. The result: in addition to the very fact of creating a software tool, its operability has been proven in terms of modeling the interface in an information system and instructions for working with it, as well as the visibility of the resulting graphical representation. The practical significance lies in the fact that this tool allows you to implement a method to counteract the deviation of user behavior by solving the optimization problem of clarifying instructions in terms of the specification of the description of interface elements; at the same time, this task is multi-criteria, since increasing the content of instructions leads to the opposite effect - complicating its perception by humans.

The purpose of the study is to determine the reliability of an employee of a critical information infrastructure entity involved in implementing measures to respond to computer incidents and eliminate the consequences of computer attacks on significant objects of the specified infrastructure, as well as to assess the feasibility of using this parameter to characterize the employee in decision support systems. As part of the solution to the problem of assigning responsible employees to implement measures to respond to computer incidents and eliminate the consequences of computer attacks, a methodological approach has been proposed to determine the reliability of the employee responsible for implementing the computer incident response plan. Practical experimental studies have been conducted to assess the effectiveness of the actions of employees of critical information infrastructure entities with different qualifications and skills. As a result of the study, an approach is proposed to calculate the main indicators of the performer's qualifications and skills, as well as to use the obtained indicators when solving the task of assigning performers (the assignment problem), which will reduce the time required to respond to a computer incident and eliminate the consequences of a computer attack. The obtained results allow for the reasonable formation of requirements for the qualifications and skills of personnel in the security forces of significant critical information infrastructure facilities and ensure the interchangeability of performers. The practical significance lies in solving the problem of optimal distribution (assignment) of an executor, taking into account their qualifications and skills, when responding to computer incidents and eliminating the consequences of computer attacks.

Problem statement. Ultra-wideband real-time local positioning systems use pulsed radio signals with an effective spectrum width of at least 500 MHz for data transmission. They feature high localization accuracy (10–30 cm) and transmission speeds (up to 27.24 Mbps, with potential for growth to 480 Mbps). This makes them an essential component in building multi-purpose systems for monitoring the movements of people and vehicles, access control (without barriers), including access to hazardous areas, etc. However, the range of such systems rapidly decreases with increasing bit rate and is also dependent on many other factors. At the same time, a universal system must be fast enough to solve problems such as vehicle collision avoidance, robot control, etc. Under these conditions, the successful application of ultra-wideband solutions requires an operational mechanism for evaluating key system parameters depending on a host of influencing factors, such as signal spectral characteristics, equivalent isotropically radiated power (EIRP) spectral density standards, transceiver settings, permissible bit error rates, etc. The goal of the work is to study the factors influencing the key parameters of ultra-wideband local positioning systems in real time and, based on this, develop an evaluation model of the transmission process as a tool for system design and maintenance. Methods used: analysis of data on influencing factors, construction and superposition of a propagation loss model and radio link budget models, working with a common model, and deriving patterns of key parameter changes at boundary values of the influencing factors. Novelty. A single common model systematizes the factors of two types of models that influence transmission range. Result. A tool for designing and maintaining ultra-wideband real-time local positioning systems has been developed, enabling prediction of their behavior under different combinations of influencing factors, in particular, ensuring maximum range at a given bit rate. Practical significance. The presented study can be used as a methodological support for classes introducing ultra-wideband real-time local positioning systems and estimating their range depending on the transmission rate and other factors.

Relevance. In the current conditions of telecommunications development, the shortwave band retains its significance as a cost-effective solution for long-range communication. At the same time, the existing methods of signal processing in HF channels require improvement in efficiency in the conditions of a complex ionospheric environment. The use of machine learning technologies opens up new opportunities for improving the quality of communication. The purpose of the study is to improve the quality of communication in the short-wave (SW) channel by applying machine learning methods for predicting ionospheric parameters and demodulating signals using OFDM technologies. The research methods include the simulation of LSTM-networks for predicting ionospheric parameters, as well as the application of convolutional (CNN) and multilayer perceptrons (MLP) for demodulating signals. The work uses quality metrics such as RMSE and BER, as well as ITU-R P.533-14 recommendations for modeling signal propagation conditions.The scientific novelty lies in a comprehensive approach to improving communication quality in the HF channel, which combines ionospheric parameter forecasting with machine learning techniques for signal demodulation. A comparative evaluation of the effectiveness of various neural network architectures in the HF channel is proposed. The results of the study showed that the use of CNN-demodulators provides the best signal reception quality at low SNR values, demonstrating a gain of up to 2.5 dB compared to the classical correlation method. LSTM-networks showed high efficiency in predicting the maximum applicable frequencies and other ionospheric parameters. The practical significance of this work is to develop methods for improving the quality of communication in the HF band, which can be used to create adaptive radio communication systems with automatic selection of operating frequencies and modulation parameters.

The relevance of this work is driven by the growing contradiction between the dynamic labor market requirements for IT competencies and the inertia of the higher education system, which calls for a systemic rather than fragmented approach to integrating IT Skills technology into the digital educational environment. The goal of the study is a systemic conceptualization of the problem field of integrating IT Skills technology into the digital educational environment of a specialized university. The research methods include theoretical analysis and synthesis of scientific literature and practical integration experience, a systemic approach that examines content, architectural, and interface aspects in their interrelation, as well as conceptual modeling methodology to substantiate the structure of information functional support for integration. The main result of the study is the systematization of three key problems –content validity, architectural compatibility, and the organization of human machine interaction – considered not in isolation but as an interconnected complex that forms a systemic barrier to the formation of relevant IT competencies in students. Based on this analysis, the object, subject, and hypothesis of the research are formulated, and three anticipated scientific outcomes are identified: a system of integration principles, an information functional architecture for the IT Skills module, and an interface organization method aimed at reducing cognitive barriers. The scientific novelty lies in the fact that, unlike existing approaches that treat content, architectural, and interface integration problems separately and propose partial solutions, this study is the first to identify and substantiate the systemic nature of these problems. The theoretical significance consists in substantiating the structure of information functional support for integration and establishing the key condition for successful integration of IT Skills technology into the digital educational environment – a system of principles that reconciles labor market requirements with pedagogical ergonomics. The practical significance is determined by the fact that the formulated hypothesis and anticipated scientific outcomes form a vector based “roadmap” for the subsequent development and implementation of information functional support aimed at overcoming the identified barriers.