Decision Support System

The National Cybersecurity Cluster of Ukraine is functionally oriented towards building systems to protect various platforms of information infrastructure, including the creation of secure technologies for detecting deepfake modifications of biometric images based on neural networks in cyberspace. 

This space proposes a conceptual approach to detecting deepfake modifications, which is deployed based on the functioning of a convolutional neural network and the classifier algorithm for biometric images structured as “sensitivity-Yuden index-optimal threshold-specificity”.

Для прийняття об’єктивних обґрунтованих рішень у всіх сферах діяльності необхідно створювати інформаційні системи підтримки прийняття рішень на основі статистичних даних і експертних оцінок та з використанням відповідних математичних моделей та методів. Запропоновано процедуру побудови інформаційної системи підтримки прийняття рішень за методологією системного аналізу на основі сучасних методів і моделей прогнозування, яка надає можливість оцінювати та прогнозувати фінансово- економічні та інші процеси в умовах впливу збурень довільних типів та різної природи.

Описано методології планування потреб у ресурсах. Проаналізовано програмні комплекси систем розподілу ресурсів і обґрунтовано потребу в розробленні своєї системи підтримки прийняття рішень. Проведено тестування прототипу СППР розподілу обмежених ресурсів, яка реалізує розроблені моделі та алгоритми.

A typical standard architecture of the support system has been proposed, making decisions on forming and implementing solutions based on cross-programming and heavy calculations and similar functional capabilities before it. The technology for disaggregating such systems on the basis of cross- programming and efficient calculations, as well as reducing costs/hours/resources for disaggregation, promotion and support of such support systems to support the adoption of a solution, has also been proposed.

The article describes the features of the VaR methodology for assessing investment risks in the financial markets of securities. Developed decision support information system allows to calculate expected and unexpected losses on selected stocks and investment portfolio as a whole, as well as to determine the probability of risk’s occurrence and the required amount of reserve capital.

This paper discusses the problems that arise when working with disparate data sources using database. The model of data warehouse is presented as way of integrating and processing data from disparate sources while creating a decision support system for the design of distributed energy systems.

This article describes the classification and approaches to the construction of DSS that take into account various aspects of the uncertainty of the development of DSS. Features of the classification were proposed and described. Generalized classification of DSS was improved. The analysis of the types of architecture, architecture reviewed information resource decision support systems, based on the principles of building a data warehouse.

This article describes an object-oriented approach of DSS modeling. Three-level architecture is suggested and it describes a conceptual model of DSS. The analysis of possible reusable components for various types of structures is analyzed. We describe the principles of building a custom DSS use of multiple components.