The article discusses modern methods for protecting bank customers' personal information based on differential anonymization of data using trusted neural networks. It provides an overview of the regulatory framework, analyzes technological approaches and describes a developed multi-level anonymization model that combines cryptographic and machine learning techniques. Special attention is paid to balancing between preserving data utility and minimizing the risk of customer identity disclosure.

Keywords: differential anonymization, trusted neural network, personal data, banking technologies, information security, cybersecurity

The article discusses current threats and vulnerabilities of telephone subscribers in the context of mass digitalization, the development of artificial intelligence and machine learning technologies, and their use in fraudulent scenarios. The study analyzes the main vulnerability factors and provides statistical data on telephone fraud incidents in Russia and abroad. Special attention is given to the phenomena of trust in authority, insufficient digital literacy, and the use of voice synthesis and deepfake technologies for social engineering attacks.

Keywords: social engineering, fraud, vishing, deepfake, artificial intelligence, digital literacy, information security

The article considers the problem of constructing a continuous displacement trajectory based on nodal feedback data in control systems with prediction of external load. The use of interpolation by cubic Fergusson splines is proposed. The proposed approach has computational efficiency and is applicable in adaptive control systems, including control of rotational movements in a non-deterministic environment.

Keywords: control, predictive models, MPC, external load, interpolation, spline, trajectory of the control object

This paper presents a decision support model for responding to forest fires in mountainous areas using fuzzy logic. The research methods include the Mamdani method for constructing a fuzzy inference system, the use of linguistic variables to describe environmental conditions and risk factors, and the formation of a rule base based on expert knowledge. The developed model implements the principles of situational management and enables determination of the fire danger level, selection of extinguishing methods, response tactics, and optimal resource allocation. Its practical significance lies in the potential application of the model in decision support systems of the Russian Ministry of Emergency Situations for operational planning and forecasting during forest fire suppression in challenging mountainous conditions.

Keywords: forest fires, mountainous terrain, fuzzy logic, decision support, intelligent systems, situational management

Construction work often involves risks when carrying out complex sets of tasks described in the form of network schedules, in particular, risks of violating tender deadlines and project costs. One of the main reasons for increased project risks is a lack of resources. The main objective of this study is to develop a methodology for modeling network schedules under resource constraints, taking into account the stochastic influence of risks on project completion deadlines. The paper analyzes tools for modeling project schedules; describes a mathematical model for estimating project cost based on a network schedule under resource constraints; proposes a method for modeling a network schedule in the AnyLogic environment; develops an algorithm for modeling parallel branches of a project schedule under resource constraints; and describes a method for modeling a network schedule for project work. Testing was conducted based on a network schedule for a project to construct a contact line support. It has been shown that the method allows for obtaining probabilistic estimates of project deadlines and costs under conditions of risk and limited resources. The methodology can be applied to various projects described by network schedules and will allow solving a number of practical tasks: optimizing resources allocated for project implementation, taking into account the time and cost of the project, analyzing risks affecting project implementation, and developing optimal solutions for project risk management.

Keywords: network schedule, work plan, simulation modeling, risk analysis, project duration, project cost

This article describes a developed method for automatically optimizing the parameters of an intelligent controller based on an adaptive genetic algorithm. The key goal of this development is to improve the mechanism for generating an intelligent controller rule base through multiparameter optimization. The genetic algorithm is used to eliminate linguistic uncertainty in the design of control systems based on intelligent controllers. A unique algorithm is proposed that implements a comprehensive optimization procedure structured in three sequential stages: identifying optimal control system parameters, optimizing the structure of the intelligent controller rule base, simulating the automatic generation process, and then optimizing the intelligent controller parameters. Implementation of this approach optimizes the weights of fuzzy logic rules and the centers of the membership functions of linguistic variables.

Keywords: intelligent controller, optimization, genetic algorithm, uncertainty, term set

The paper discusses issues related to the use of graph-theoretic models in text analysis. One of the tasks is to aggregate such models to identify more "simple" graphs, the vertices of which correspond to subsets of the vertices of the original model, and the edges reflect the "strong connections" between the vertices. Using the example of a Russian folk tale plot, it is shown how to build an aggregated model with a given threshold of significance and present it for further analysis. To conduct the experiments, a set of graph-theoretical models for fairy-tale plots from the collection of A.M. Afanasyev was built using the Folklore information system, where the graph aggregation module was improved.

Keywords: text analysis, graph-theoretical model, aggregation, significance threshold, storage format, folklore text, fairy tale plot, information system "Folklore"

The article deals with the problem of quantifying the security of objects of the penal correction system based on mathematical modeling. The authors propose a modified genetic algorithm in which the traditional fitness function is replaced by a mechanism of "virtual movement" of individuals in a discrete space, which allows taking into account both the individual characteristics of safety measures and their cumulative impact. A step-by-step example of applying the algorithm to choosing the optimal set of protective measures based on expert assessments based on several criteria is given. The results demonstrate the effectiveness of the proposed approach for solving multi-criteria tasks of assessing and improving security in conditions of uncertainty and the absence of an explicit analytical relationship between system parameters.

Keywords: security, vulnerability, event, penal enforcement system, genetic algorithm, mathematical modeling, optimization, expert assessment, criterion, security, security regime, discrete space, coalition, crossing, fitness function

Information technologies have become increasingly used in various fields, be it document management or payment systems. One of the most popular and promising technologies is cryptocurrency. Since they require ensuring the security and reliability of data in the system, most of them use blockchain and complex cryptographic protocols, such as zero-knowledge proof protocols (ZKP). Therefore, an important aspect for achieving the security of these systems is verification, since it can be used to assess the system's resistance to various attacks, as well as its compliance with security requirements. This paper will consider both the concept of verification itself and the methods for its implementation. A comparison of methods for identifying a proof suitable for zero-knowledge protocols is also carried out. And as a result, a conclusion is made that an integrated approach to verification is needed, since choosing only one method cannot cover all potential vulnerabilities. In this regard, it is necessary to apply various verification methods at various stages of system design.

Keywords: cryptocurrency, blockchain, verification, formal method, static analysis, dynamic method, zero-knowledge proof protocol

This paper proposes a novel model of computer network behavior that incorporates weighted multi-label dependencies to identify rare anomalous events. The model accounts for multi-label dependencies not previously encountered in the source data, enabling a "preemptive" assessment of their potential destructive impact on the network. An algorithm for calculating the potential damage from the realization of a multi-label dependency is presented. The proposed model is applicable for analyzing a broad spectrum of rare events in information security and for developing new methods and algorithms for information protection based on multi-label patterns. The approach allows for fine-tuning the parameters of multi-label dependency accounting within the model, depending on the specific goals and operating conditions of the computer network.

Keywords: multi-label classification, multi-label dependency, attribute space, computer attacks, information security, network traffic classification, attack detection, attribute informativeness, model, rare anomalous events, anomalous events

Many major cities around the world are seeing a trend toward compact housing units, typically located in central areas and fully integrated with existing urban infrastructure. Despite similarities in size and location, each project offers unique architectural and social solutions to address the housing crisis and adapt to limited space. With urban density increasing and real estate prices rising, compact housing projects, typically located in central areas and fully integrated with existing infrastructure, are becoming increasingly relevant. Despite the general trend toward smaller spaces, each project offers unique architectural and social responses to the challenges of modern urbanism.

Keywords: micro-housing, urbanization, architecture, city, infrastructure, mobility, sustainability, renovation, miniaturization, accessibility, autonomy, flexibility, project, space, concept

The article discusses the development of a method for protecting confidential images in instant messengers based on masking with orthogonal matrices. The vulnerability of the system to brute-force attacks and account compromise is analyzed. The main focus is on the development of an architecture for analyzing abnormal activity and adaptive authentication. The article presents a system structure with independent security components that provide blocking based on brute-force attacks and flexible session management. The interaction of the modules within a unified security system is described, with the distribution of functions between server and client components.

Keywords: information security, messenger, messaging, communications, instant messaging systems, security audits, and brute-force attacks

The article presents a comparative analysis of the performance of three solver programs (based on the libraries lpSolve, Microsoft Solver Foundation and Google OR-Tools) when solving a large-dimensional linear Boolean programming problem. The study was conducted using the example of the problem of identifying the parameters of a homogeneous nested piecewise linear regression of the first type. The authors have developed a testing methodology that includes generating test data, selecting hardware platforms, and identifying key performance metrics. The results showed that Google OR-Tools (especially the SCIP solver) demonstrates the best performance, surpassing analogues by 2-3 times. The Microsoft Solver Foundation has shown stable results, while the lpSolve IDE has proven to be the least productive, but the easiest to use. All solvers provided comparable accuracy of the solution. Based on the analysis, recommendations are formulated for choosing a solver depending on performance requirements and integration conditions. The article is of practical value for specialists working with optimization problems and researchers in the field of mathematical modeling.

Keywords: regression model, homogeneous nested piecewise linear regression, parameter estimation, method of least modules, linear Boolean programming problem, index set, comparative analysis, software solvers, algorithm performance, Google OR-Tools

The article is devoted to the development of an innovative neural network decision support system for firefighting in conditions of limited visibility. A comprehensive approach based on the integration of data from multispectral sensors (lidar, ultrasonic phased array, temperature and hygrometric sensors) is presented. The architecture includes a hybrid network that combines three-dimensional convolutional and bidirectional LSTM neurons. To improve the quality of processing, a cross-modal attention mechanism is used to evaluate the physical nature and reliability of incoming signals. A Bayesian approach is used to account for the uncertainty of forecasts using the Monte Carlo dropout method. Adaptive routing algorithms allow for quick response to changing situations. This solution significantly improves the efficiency of firefighting operations and reduces the risk to personnel.

Keywords: mathematical model, intelligence, organizational model, gas and smoke protection service, neural networks, limited visibility, fire department, management, intelligent systems, decision support

Problem statement. When modeling a complex technical system, the issues of parameter estimation are of primary importance. To solve this problem, it is necessary to obtain a methodology that allows eliminating errors and inaccuracies in obtaining numerical parameters. Goal. The article is devoted to a systematic analysis of the methodology for estimating the parameters of a complex technical system using the interval estimation method. The research method. A systematic analysis of the methods of using interval estimates of numerical parameters is carried out. The decomposition and structuring of the methods were carried out. Results. The expediency of using a methodology for describing the parameters of a complex technical system using the interval estimation method is shown. An analysis of the use of various interval estimation models is presented. Practical significance. Application in the analysis and construction of complex systems is considered as a practical application option. The method of estimating the parameters of a complex technical system using the interval estimation method can be used as a practical guide.

Keywords: interval estimation, parameter estimation, numerical data, fuzzy data, complex technical systems