This paper deals with problems of the development and security of distributed information systems. It explores the challenges of risk modeling in such systems and suggests a risk-modeling approach that is responsive to the requirements of complex, distributed, and large-scale systems. This article provides aggregate information on various risk assessment methodologies; such as quantitative, qualitative, and hybrid methods; a comparison of their advantages and disadvantages; as well as an analysis of the possibility of application in distributed information systems. It also presents research on a comprehensive, dynamic, and multilevel approach to cyber risk assessment and modeling in distributed information systems based on security metrics and techniques for their calculation, which provides sufficient accuracy and reliability of risk assessment and demonstrates an ability to solve problems of intelligent classification and risk assessment modeling for large arrays of distributed data. The paper considers the main issues and recommendations for using risk assessment techniques based on the suggested approach.

Cybersecurity risk assessment and analysis is an important element for building an effective information security management system. The high complexity and scalability of the architecture of modern distributed systems, the heterogeneity of equipment and infrastructure, as well as constant changes in the configuration and scaling of the environment give rise to a number of problems related to the collection and analysis of information for risk assessment, the need for operational processing of large arrays of complex in structure and heterogeneous in nature data coming from differentiated security and monitoring systems, event logs, audit reports and other sources, as well as the lack of a single format for their presentation. The limitations of existing standards and methodologies in the dynamic conditions of modern DIS, their conceptual nature and the complexity of practical implementation and application require the development of flexible methodological and technological solutions for cyber risk analysis that would integrate the advantages of existing approaches, provide automation of calculations and take into account the dynamic aspects of distributed environment. The article presents a comprehensive adaptive method for quantitative assessment of cybersecurity risks in distributed information systems, which is relevant in dynamic conditions of complex multi-component and scalable DIS. The proposed method, integrating a metric-oriented approach based on the results of a complex of neural network models for assessing DIS infrastructure security indicators and compliance metrics for regulatory frameworks and leading standards, provides an opportunity to create a scalable and dynamic cyber risk management system that effectively responds to modern threats in DIS and open opportunities for the comprehensive implementation of intelligent information security management systems in risk management processes.

Оцінка та аналіз ризиків кібербезпеки є фундаментальними аспектами формування надійної і ефективної СУІБ, особливо в умовах стрімкого розвитку технологій та зростання складності сучасних РІС. Традиційні методи оцінки ризиків, що засновані переважно на концептуальних підходах і класичних методах, мають ряд обмежень та є малоефективними в умовах сучасних масштабованих розподілених систем, оскільки не враховують динаміку середовища та не забезпечують ефективний аналіз взаємозв’язків між численними факторами ризику. В дослідженні запропоновано метод побудови профілю ключових факторів ризику сучасних розподілених інформаційних систем на основі урахування кореляційного аналізу та моделювання їх взаємозв’язків, що дозволяє підвищити ефективність процесу оцінки ризиків кібербезпеки в умовах динамічного середовища сучасних масштабованих розподілених інформаційних систем. На основі запропонованого методу здійснено розробку профілю ключових факторів ризику сучасних розподілених систем, проведено аналіз їх статистичної важливості та кореляції, а також визначено і структуровано основні заходи та контролі інформаційної безпеки, які демонструють найкращі показники ефективності в умовах розподіленості середовища, враховують як технологічні, так і організаційні аспекти, забезпечуючи системний підхід до управління ризиками ІБ, зменшення впливу загроз і підвищення стійкості розподілених систем до можливих атак. Запропонований підхід до оптимізації вибору вхідного набору ознак та виокремлення найбільш вагомих факторів ризику на основі спроектованого профілю ключових факторів ризику для сучасних РІС продемонстрував тотожний результат по числовому показнику кількості відібраних для аналізу метрик у порівнянні з факторним аналізом за допомогою методу головних компонент (PCA) – 42 метрики у порівнянні із 40 для PCA, але при цьому забезпечив покращення загальних показників точності класифікації для проєктованих моделей оцінки ризику кібербезпеки в РІС на 4% у порівнянні з контрольною моделлю на основі PCA, що підтверджує його ефективність у контексті адаптивного аналізу ризиків у розподілених середовищах.

In modern conditions of information systems functioning, the rapid growth of scale, complexity and distribution of computing resources is becoming one of the defining trends in the development of digital infrastructure. Within the framework of the widespread implementation of complex multi-component information systems that are distributed in nature and contain a large number of nodes, as well as a significant increase in the number and complexity of cyber threats focused on scalable systems, cybersecurity risks should be considered as a key factor in strategic planning of business processes. Regular analysis and assessment of cybersecurity risks allows determining the necessary and sufficient set of information protection tools, regulatory and organizational mechanisms to reduce information security threats, and ensures the process of building the most effective architecture of a comprehensive information security management system. Existing tools and assessment methodologies, which are mostly conceptual in nature and based on statistical approaches, are ineffective in analysis of large arrays of high-dimensional heterogeneous data and metrics of distributed systems. The article focuses on the current trends and existing approaches to information security risk assessment in distributed information systems. It analyzes the importance of risk management in the process of ensuring information security, and also describes a core principles of intelligent security risk assessment in distributed information systems based on the neural network approach. Research also presents a dynamic and comprehensive model of cyber risk assessment in distributed information systems based on back propagation neural network architecture and several methods of its optimization, which provides sufficient accuracy and reliability of risk assessment in the conditions of analysis of large arrays of heterogeneous input data.

B a c k g r o u n d . Cyber-Physical Systems (CPS) play an important role in today's technology, as they combine physical objects and cryptographic security mechanisms to ensure the secure operation of networked devices, particularly in the financial industry, the Internet of Things (IoT), and the Industrial Internet of Things (IIoT). The main problem of such systems is to ensure reliable and effective data protection with limited resources of computing power and energy consumption. Cryptographic protocols used in cyber-physical systems must be highly efficient, because both the security and the overall performance of the systems depend on their operation. This article is aimed at researching ways to improve the efficiency of cryptographic protocols in KFS. R e s u l t s . During the research, it was established that: the use of MTLS protocols increases the level of data protection, but at the same time requires a much larger amount of CFS resources compared to TLS and SSL. At the same time, TLS still uses more capacity of cyber-physical systems than SSL, which increases the cost of CFS devices. Optimizing encryption and decryption algorithms in the TLS protocol can help reduce device costs and increase data transfer speeds. C o n c l u s i o n s The obtained results show that increasing the efficiency of cryptographic protocols in cyber-physical systems is possible by using more effective encryption algorithms. Optimizing security protocols can significantly improve the data transfer rate and performance of cyber-physical systems, especially in resource-constrained environments. It is worth paying attention to the concept of using existing security protocols that combine the use of symmetric and asymmetric encryption algorithms. In the future, it is the speed of encryption and decryption that will play a significant role in increasing efficiency. Since it is this factor that will reduce the use of resources in the CFS and will also gain an advantage in time, due to the transfer of more information per unit of time, with almost no loss in crypto-resistance. Further research may focus on the development.