The article analyzes the parameters of social networks. The analysis is performed to identify critical threats. Threats may lead to leakage or damage to personal data. The complexity of this issue lies in the ever-increasing volume of data. Analysts note that the main causes of incidents in Internet resources are related to the action of the human factor, the mass hacking of IoT devices and cloud services. This problem is especially exacerbated by the strengthening of the digital humanistic nature of education, the growing role of social networks in human life in general. Therefore, the issue of personal information protection is constantly growing. To address this issue, let’s propose a method of assessing the dependence of personal data protection on the amount of information in the system and trust in social networks. The method is based on a mathematical model to determine the protection of personal data from trust in social networks. Based on the results of the proposed model, modeling was performed for different types of changes in confidence parameters and the amount of information in the system. As a result of mathematical modeling in the MatLab environment, graphical materials were obtained, which showed that the protection of personal data increases with increasing factors of trust in information. The dependence of personal data protection on trust is proportional to other data protection parameters. The protection of personal data is growing from growing factors of trust in information. Mathematical modeling of the proposed models of dependence of personal data protection on trust confirmed the reliability of the developed model and proved that the protection of personal data is proportional to reliability and trust

To effectively protect critical infrastructure facilities (CIF), it is important to understand the focus of cybersecurity efforts. The concept of building security systems based on a variety of models describing various CIF functioning aspects is presented. The development of the concept is presented as a sequence of solving the following tasks. The basic concepts related to cyberattacks on CIF were determined, which make it possible to outline the boundaries of the problem and determine the level of formalization of the modeling processes. The proposed threat model takes into account possible synergistic/emergent features of the integration of modern target threats and their hybridity. A unified threat base that does not depend on CIF was formed. The concept of modeling the CIF security system was developed based on models of various classes and levels. A method to determine attacker's capabilities was developed. A concept for assessing the CIF security was developed, which allows forming a unified threat base, assessing the signs of their synergy and hybridity, identifying critical CIF points, determining compliance with regulatory requirements and the state of the security system. The mathematical tool and a variety of basic models of the concept can be used for all CIFs, which makes it possible to unify preventive measures and increase the security level. It is proposed to use post-quantum cryptography algorithms on crypto-code structures to provide security services. The proposed mechanisms provide the required stability (230–235 group operations), the rate of cryptographic transformation is comparable to block-symmetric ciphers (BSC) and reliability (Perr 10–9–10–12) Для эффективной защиты объектов критической инфраструктуры (ОКИ) важно понимать направленность усилий по кибербезопасности. Представлена концепция построения систем безопасности, базирующиеся на множестве моделей, описывающих различные стороны функционирования ОКИ. Разработка концепции представлена в виде последовательности решения следующих задач. Определены основные понятия, связанные с кибератаками на ОКИ, которые позволяют очертить границы проблемы и определить уровень формализации процессов моделирования. Предложенная модель угроз учитывает возможные синергетические/эмерджентные особенности комплексирования современных целевых угроз и их гибридность. Сформирована унифицированная база угроз, которая не зависит от ОКИ. Разработана концепция моделирования системы безопасности ОКИ, которая основана на множестве моделей различных классов и уровней. Разработана методика, которая позволяет определить возможности нападающего. Разработана концепция оценки уровня защищенности ОКИ, что позволяет сформировать унифицированную базу угроз, оценить признаки их синергизма и гибридности, выявить критические точки в инфраструктуре ОКИ, определить уровень выполнения требований регуляторов, и состояние системы защиты. Математический аппарат и множество моделей, лежащих в основе концепции, возможно использовать для всех ОКИ, что позволяет унифицировать превентивные меры и повысить уровень безопасности. Предложено использование алгоритмов постквантовой криптографии на крипто-кодовых конструкциях для обеспечения услуг безопасности. Предложенные механизмы обеспечивают уровень устойчивости (230–235 групповых операций), скорость криптопреобразования сравнима с БСШ и достоверности (Pош 10-9–10-12). Для ефективного захисту об’єктів критичної інфраструктури (ОКІ) важливо розуміти спрямованість зусиль з кібербезпеки. Представлена концепція побудови систем безпеки, що базуються на множині моделей, що описують різні сторони функціонування об’єкта захисту. Розробка концепції наведена у вигляді послідовності рішення наступних завдань. Визначено основні поняття, пов’язані з кібертерористичними атаками на ОКІ, які дозволяють окреслити межі проблеми і визначити рівень формалізації процесів моделювання. Модель загроз, що запропонована, дозволяє врахувати можливі синергетичні/емерджентні...

One of the pressing areas that is developing in the field of information security is associated with the use of Honeypots (virtual decoys, online traps), and the selection of criteria for determining the most effective Honeypots and their further classification is an urgent task. The main products that implement virtual decoy technologies are presented. They are often used to study the behavior, approaches and methods that an unauthorized party uses to gain unauthorized access to information system resources. Online hooks can simulate any resource, but more often they look like real production servers and workstations. A number of fairly effective developments are known that are used to solve the problems of detecting attacks on information system resources, which are based on the apparatus of fuzzy sets. They showed the effectiveness of the appropriate mathematical apparatus, the use of which, for example, to formalize the approach to the formation of a set of reference values that will improve the process of determining the most effective Honeypots. For this purpose, many characteristics have been formed (installation and configuration process, usage and support process, data collection, logging level, simulation level, interaction level) that determine the properties of online traps. These characteristics became the basis for developing a method for the formation of standards of linguistic variables for further selection of the most effective Honeypots. The method is based on the formation of a Honeypots set, subsets of characteristics and identifier values of linguistic estimates of the Honeypot characteristics, a base and derived frequency matrix, as well as on the construction of fuzzy terms and reference fuzzy numbers with their visualization. This will allow classifying and selecting the most effective virtual baits in the future.

Sustainable urban development increasingly relies on hyperlocal environmental analytics created by smart city platforms that combine stationary and mobile sensors, Earth observations, meteorology, and land-use data. However, accurate spatio-temporal resolution can provide indirect identification and amplify cybersecurity threats. This article proposes the regulatory and technical mapping that implements the General Data Protection Regulation (GDPR) and the Network and Information Security Directive (NIS2) throughout the lifecycle of environmental data—reception, transport, storage, analytics, sharing, and publication. The methods combine doctrinal legal analysis, a review of the scope of recent research, formalized compliance modeling, modeling with synthetic city-scale datasets, expert identification, and demonstration of integrated analytics. The demonstration links deep evaluation of neural abnormalities (convolutional plus recurrent layers), short-term Fourier transformation of sensor signals, byte-to-image telemetry fingerprints, and protocol event counters, thereby tracking detection to explanatory evidence and to control actions. Deliverables include a matrix aligning lifecycle stages with GDPR principles and rights, as well as with the responsibilities of NIS2; a checklist for assessing the impact on data protection, which takes into account the risks of fairness and stigmatization; a basic set of controls for identification and access, secure design, monitoring, continuity, supplier assurance, and incident reporting; as well as a multi-layered publishing strategy that combines transparency with privacy through aggregation, delayed release, differentiated privacy budgets, and research enclaves. The visualization confirms that technical signals can be included in audit-ready reporting and automated response, while the guidelines legally clarify the relevant bases for common use cases such as air quality assurance networks, noise mapping, citizen sensor applications, and mobility and exposure modeling. The effects of the policy emphasize shared services for small municipalities, supply chain security, and ongoing review to counteract the mosaic effect. Overall, the study shows how cities can maximize environmental and social value based on environmental data, while maintaining privacy, sustainability, and equity by design.

The primary research goal is to develop a method for constructing a classification model of modern approaches to implementing sociotechnical attacks, to systematize and integrate existing classifications of relevant approaches, with the possibility of expanding with new characteristic features. The development of information technology and data exchange creates new threats to cyber security, including cyber attacks and frauds. Social networks and artificial intelligence contribute to the improvement of sociotechnical methods. Analyzing the data of leading studies, certain methods are identified that social engineers use most often, but these publications do not form a set of signs that characterize the approaches to implementation of the corresponding attacks, which will make it possible to formalize the process of their classification from a systemic standpoint. The research is aimed at solving the following tasks: toconstruct a model for classifying sociotechnical attacks in which it is possible to develop a generalized hierarchical model; to form a generalized set of features, criteria, and sub-criteria, which allows us to select and develop appropriate means of countering sociotechnical attacks from a systemic perspective; and to carry out the modelling of a corresponding cyberattack for a systematic understanding of actions and countermeasures. Given this, the analysis and classification of modern approaches to the implementation of sociotechnical attacks is an important component of a cyber security strategy to ensure protection against ever-growing threats and is an urgent scientific task. Results and conclusions. Based on the multi-theoretical approach, a method is proposed, in which, due to the stages of determining the set: identifiers of signs, criteria, and sub-criteria, it is possible to develop a generalized hierarchical model for classifying socio-technical attacks according to the characteristic principle. Based on the proposed model and the analyzed literature, a generalized set of features, criteria, and sub-criteria has been formed, such as: time aspect, industry affiliation, interaction with security policy, remoteness, initialization, tools, manipulation, violation of characteristics, relational signs, severity level, type of attacked source, type of access, type of appeal, type of sociotechnical technique, and scale, which allows us to select and develop appropriate means of countering sociotechnical attacks from a systemic perspective. The example of conducting a sociotechnical attack is considered, in which, taking into account the MAISA classification model and such steps of their implementation as: target research, preparation of a sociotechnical attack, performing of the attack, exploitation of the information received, hiding traces, made it possible to approach the understanding of the actions of a sociotechnician when implementing a phishing attack from a systemic perspective for the further development of appropriate countermeasures. In addition, based on the obtained criteria, it is possible to develop a method for assessing personnel readiness to counter various classes of sociotechnical attacks.

The S-box is a key component of modern ciphers, determining the quality and performance of the cryptographic algorithms in which it is applied. Many constructions for synthesizing high-quality S-boxes have been established, and those based on Galois fields theory—for example, the Nyberg construction applied in the AES cryptographic algorithm—are particularly important. An integral component of the Nyberg construction is the affine transformation, which is used to improve the avalanche and correlation properties of the S-box. In this paper, a new approach is adopted for synthesizing affine transformations for S-boxes based on the quaternary matrices over the Galois field GF(4). We describe four basic structures that serve as the foundation for synthesizing a complete class of 648 affine transformation matrices of order n = 3 and a class of 7776 matrices of order n = 4 and introduce a recurrent structure to facilitate the synthesis of matrices for higher orders. Using these matrices in combination with the Nyberg construction, it is possible to construct bijective S-boxes that outperform the original Nyberg construction and many other known S-boxes in terms of strict avalanche criterion (SAC) and bit independence criterion strict avalanche criterion (BIC SAC) values, while maintaining a maximal level of nonlinearity and good cryptographic properties. We also propose modified GF(4) affine transformations that can be applied to specialized S-boxes which already satisfy the SAC for both component Boolean and 4-functions, as well as the criterion of minimal correlation between input and output, allowing us to enhance their nonlinearity to the value of N_f = 96. We integrate the synthesized S-boxes into the AES algorithm and evaluate their practical performance. The encryption outputs successfully pass the NIST statistical test suite in 96 out of 100 cases, outperforming both the original AES S-box and other reference constructions, confirming the practical strength of the proposed method.