Risk Management of Information Threats in IT with the Help of Intelligent Disinformation Detection Systems

Authors

DOI:

https://doi.org/10.31861/sisiot2024.2.02004

Keywords:

intelligent system, disinformation detection, artificial intelligence, machine learning, deep learning

Abstract

The article describes an intelligent disinformation detection system that counteracts the spread of false information on the Internet. It uses modern text and data processing methods, including machine learning and natural language processing, to accurately identify fake news. The main function of the system is to provide a predictive assessment of the reliability of information, which helps users make informed decisions, minimising the risk of falling under the influence of disinformation. Real-world testing of the system has confirmed its ability to quickly identify fake information, contributing to the information literacy of users and raising their awareness of information threats. Such a system is an important element in strengthening information security, which is especially important for Ukraine in the face of numerous information challenges. The system also plays an important role in managing the risks of information threats in IT. The results of the study made it possible to identify potential threats in the form of disinformation that could be used to manipulate public opinion or undermine trust in institutions. Integration of intelligent systems into risk management processes allows for a timely response to threats, reducing their impact on IT infrastructure and preserving the reputation of organisations. The system can be applied not only in the IT sector, but also in journalism, education, and public administration, where it helps prevent disinformation that has a serious social impact. It can also be used to monitor and analyse information flows, which helps identify and counteract false information. Thus, the developed system is an important step in strengthening information security, providing protection against fake news and serving as an effective tool for managing the risks of information threats in today's digital society.

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Author Biographies

  • Dmytro Uhryn, Yuriy Fedkovych Chernivtsi National University

    Graduated from Yuriy Fedkovych Chernivtsi National University, Chernivtsi. He is currently a Doctor of Technical Sciences, Professor, Associate Professor at Yuriy Fedkovych Chernivtsi National University. Research interests: data mining, decision support information technologies, swarm intelligence systems, industry-specific geographic information systems.

  • Yuriy Ushenko, Yuriy Fedkovych Chernivtsi National University

    Prof., Computer Science Department, Chernivtsi National University, Chernivtsi, Ukraine. Research Interests: Data Mining and Analysis, Computer Vision and Pattern Recognition, Optics & Photonics, Biophysics.

  • Myroslav Kovalchuk, Yuriy Fedkovych Chernivtsi National University

    Candidate of Physical and Mathematical Sciences, Associate Professor at the Department of Computer Science, Yuriy Fedkovych Chernivtsi National University. His research interests include neural networks, the development of information systems, and the organization of databases.

  • Mykyta Zakharov, Yuriy Fedkovych Chernivtsi National University

    PhD student, Computer Science Department, Chernivtsi National University, Chernivtsi, Ukraine. Has publications in student scientific conferences. Research Interests: Data Mining, Artificial Intelligence and Analysis.

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Published

2024-12-30

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Articles

How to Cite

[1]
D. Uhryn, Y. Ushenko, M. Kovalchuk, and M. Zakharov, “Risk Management of Information Threats in IT with the Help of Intelligent Disinformation Detection Systems”, SISIOT, vol. 2, no. 2, p. 02004, Dec. 2024, doi: 10.31861/sisiot2024.2.02004.

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