Електронний репозитарій ПДАУ
Полтавський державний аграрний університет
Електронний репозитарій (сховище, архів) наукових публікацій – електронний архів результатів науково-дослідної роботи, публікацій науковців, викладачів, аспірантів та студентів університету, кваліфікаційних робіт студентів для їх централізованого зберігання та надання відкритого доступу до них світовій академічній спільноті у режимі онлайн.
Нові надходження
Automating requirements traceability in project documentation using TraceTrend tool: model, design and application
(Radioelectronic and Computer Systems, 2025) Odarushchenko, O. M.; Odarushchenko, O. B.; Одарущенко, Олег Миколайович; Одарущенко, Олена Борисівна
The object of the study is a formalized model of requirements traceability in project documentation for hardware-software systems. The subject matter of the research encompasses the application of mathematical modeling and tool-based approaches to automate the traceability process, focusing on the design and functionality of the TraceTrend software tool. The primary goal of the study is to improve the quality and integrity of requirements management by implementing traceability mechanisms that ensure logical consistency, hierarchical correctness, and complete test coverage across all project documentation stages. The research tasks include: identifying challenges related to manual requirements tracing in safety-critical domains; constructing a formal mathemat-ical model based on set theory, binary relations, and directed graphs; defining binary matrices for requirement inheritance and test coverage; developing automated analysis techniques for traceability conditions; integrating the model into the TraceTrend tool; and demonstrating its applicability through a real-world case study. The study employed the following methods: mathematical modeling of binary relations, model-based testing, static analysis of documentation structures, and the use of Boolean matrix operations for verifying coverage and con-sistency. As a result of the research, a formal model of requirements traceability was created and implemented in the TraceTrend tool.
Development of a method for detecting cyber attacks on information systems based on artificial intelligence technologies
(Eastern-European Journal of Enterprise Technologies, 2025) Odarushchenko, O. B.; Одарущенко, Олена Борисівна
The object of this research is arti¬ficial immune systems. The problem addressed in the study is improving the responsiveness of cyberattack detection in information systems while ensuring a predetermined level of convergence, regardless of the num¬ber of destabilizing factors. The sub-ject of the research is the cyberattack detection process.
A cyberattack detection method for information systems based on arti-ficial intelligence technologies is pro¬posed. The originality of the method lies in the use of additional enhanced procedures that allow:
– initializing the initial popula¬tion of swarm agents and verifying information system parameters using an improved bat algorithm, which minimizes the error of entering incor¬rect data concerning the operational information system of military forces;
– performing initial identification of attacks specific to the given infor-mation system using a decision tree;
– adapting to the type and dura¬tion of cyberattacks through multi-lev¬el adaptation of the artificial immune system;
– conducting initial selection of antibodies for each swarm of the artificial immune system using an improved genetic algorithm;
– training general-swarm anti¬bodies using elite-swarm antibodies, thereby enabling deep learning;
– replacing unfit individuals for search through antibody population renewal;
– performing simultaneous solu¬tion search in multiple directions;
– calculating the required amount of computational resources in cases where available resources are insuf¬ficient for the necessary calculations.
An example application of the proposed method was conducted for cyberattack detection in an operation¬al military force group. The results demonstrated an average increase in detection accuracy by 16%, an aver-age improvement in responsiveness by 12%, and a high result convergence level of 95.23%
Development of a solution search method using artificial intelligence
(Eastern-European Journal of Enterprise Technologies, 2024-04-30) Odarushchenko, O. B.; Одарущенко, Олена Борисівна
The object of the study is decision sup¬port systems.
The problem of increasing decision-mak¬ing efficiency in conditions of uncertainty and a set of different parameters was solved using a bio-inspired algorithm.
The subject of the study is the deci¬sion-making process in management prob¬lems using the heron flock algorithm, the improved genetic algorithm and evolving artificial neural networks.
A solution search method using the improved heron flock algorithm is pro¬posed. The study is based on the heron flock algorithm to find a solution regarding the object state. Evolving artificial neural networks are used to train the heron flock algorithm, and an advanced genetic algo¬rithm is used to select the best individuals of the heron flock. The method has the fol¬lowing sequence of actions:
– input of initial data;
– setting agents on the search plane;
– numbering heron agents in the flock;
– setting the initial velocity of heron agents;
– waiting strategy for heron agents;
– aggressive strategy;
– checking the discriminatory condition;
– selection of the best individuals from the heron flock;
– ranking and sorting the obtained so-lutions;
– training heron knowledge bases;
– determining the amount of necessary computing resources of the intelligent deci¬sion support system.
Method of Assessing the State of Hierarchical Objects based on Bio-Inspired Algorithms
(Advanced Information Systems, 2023) Odarushchenko, O. B.; Одарущенко, Олена Борисівна
Nowadays, no state in the world is able to work on the creation and implementation of artificial intelligence in isolation from others. Artificial intelligence technologies are actively used to solve both general and highly specialized tasks in various spheres of society. In the process of assessing (identifying) the state of complex and objects of analysis and management, there is a high degree of a priori uncertainty regarding their state and a small amount of initial data describing them. At the same time, despite the huge amount of information, the degree of non-linearity, illogicality and noisy data is increasing. That is why the issue of improving the efficiency of assessing the condition of complex and objects is an important and urgent issue. The object of research is the objects of analysis. The subject of the research is the identification and forecasting of the analysis objects state with the help of bio-inspired algorithms. In the research, the evaluation and forecasting method was developed using fuzzy cognitive maps and the genetic algorithm.
Application of Formal Verification Methods in a Safety-Oriented Software Development Life Cycle
(Proceedings of the 13th IEEE Conference Dependable Systems, Services and Technologies, DESSERT2023, Athens, Greece, 2023-10-14) Odarushchenko, O. B.; Одарущенко, Олена Борисівна
This article delves into the growing significance of ensuring reliability and functional safety in hardware and embedded software of programmable controllers amidst rapid technological advancement. With the rise of FPGA-based digital Instrumentation and Control Systems (ICS), the need for dependable solutions has led to the development of the RadICS FSC (Functional Safety Controller) Platform by LLC RPC Radiy. While programmable controllers are pivotal across industries, vulnerabilities in their embedded software can lead to dire consequences for safety, economy, and the environment, particularly in safety-critical applications. Given this backdrop, testing embedded software becomes integral to ensuring reliability and safety. Tailored testing approaches are essential due to the unique characteristics of hardware, software, and specific controller applications. These approaches must encompass functional aspects as well as potential vulnerabilities exploitable by malicious actors.