Devising a method for detecting information threats in the Ukrainian cyber space based on machine learning

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.317456

Keywords:

information threat, fake news, machine learning, disinformation detection, dataset, cyber security

Abstract

The object of this study is a disinformation detection process based on search algorithms for identifying fake news. The main task was to define a set of criteria and parameters for detecting the Ukrainian-language disinformation based on machine learning. A methodology has been considered for developing and filling a dataset of fakes for further training of the model and testing it for the purpose of identifying disinformation and propaganda, as well as determining the attributes of primary sources and routes of their distribution. This makes it possible to reasonably approach the definition of a model for forecasting the development of information threats in the cyberspace of Ukraine. In particular, the accuracy of automatic detection of the probability of disinformation in texts can be increased. For the English-language texts using balanced datasets for training when applying classical machine learning classifiers, the accuracy of identification and recognition of fakes is ³90 %, and for the Ukrainian-language texts – ³52 % and £90 %. That has made it possible to devise requirements for the structure and content of a typical dataset of fakes in the period after the full-scale invasion of Ukraine. The practical result of this work is the designed decision-making support system for monitoring, detecting, recognizing, and forecasting information threats in the cyberspace of Ukraine based on NLP and machine learning. The implementation of preliminary processing of the Ukrainian-language news, taking into account the linguistic features of the language in the text, increases the accuracy of fake identification by »1.72 times. Approaches to the construction of models for forecasting the development of information threats in cyberspace have been developed, which is an urgent task when fake news and information manipulation can affect public sentiment, politics, and the economy

Author Biographies

Victoria Vysotska, Lviv Polytechnic National University

PhD, Associate Professor

Department of Information Systems and Networks

Mariia Nazarkevych, Lviv Polytechnic National University

Doctor of Technical Sciences, Professor

Department of Information Systems and Networks

Serhii Vladov, Kremenchuk Flight College of Kharkiv National University of Internal Affairs

PhD

Department of Scientific Activity Organization

Olga Lozynska, Lviv Polytechnic National University

PhD, Associate Professor

Department of Information Systems and Networks

Oksana Markiv, Lviv Polytechnic National University

PhD, Associate Professor

Department of Information Systems and Networks

Roman Romanchuk, LLC TIETO UKRAINE SUPPORT SERVICES

Head of Projects and Programs in the Field of Non-Material Production

Vitalii Danylyk, Genesis Space

Full-Stack Developer

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Devising a method for detecting information threats in the Ukrainian cyber space based on machine learning

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Published

2024-12-25

How to Cite

Vysotska, V., Nazarkevych, M., Vladov, S., Lozynska, O., Markiv, O., Romanchuk, R., & Danylyk, V. (2024). Devising a method for detecting information threats in the Ukrainian cyber space based on machine learning. Eastern-European Journal of Enterprise Technologies, 6(2 (132), 36–48. https://doi.org/10.15587/1729-4061.2024.317456

Issue

Vol. 6 No. 2 (132) (2024): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2024 Victoria Vysotska, Mariia Nazarkevych, Serhii Vladov, Olga Lozynska, Oksana Markiv, Roman Romanchuk, Vitalii Danylyk

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