Design of an intelligent module for detecting signs of information security threats and the emergence of unreliable data

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.317000

Keywords:

information-computer system, automated modeling, control, artificial intelligence, flexible production system

Abstract

At the stage of production preparation, there is an urgent need for an automated system that would timely detect signs of threats to information security and the emergence of unreliable data. To solve this problem, an intelligent module capable of detecting such threats and unreliable and/or anomalous data has been designed. The proposed intelligent module is the state-of-art, original, and effective toolkit. It can be recommended for practical use as part of the well-known information and computer system for automated modeling of the system of automatic orientation of production objects at the stage of technological preparation of machine and instrument-building production. Its application makes it possible to increase information security and reliability of important production data at the stage of technological preparation of production, in particular, when modeling systems for automatic orientation of production objects. In addition, the use of the proposed intelligent module makes it possible to obtain a number of important social and economic effects. Some of these effects are manifested in the prevention or reduction of material, intellectual and time costs for saving and restoring information, etc.

Automated analysis of important production data regarding their reliability and abnormality is carried out by machine learning methods using a specially designed advanced variational autoencoder based on classification algorithms and using wavelet transformation.

The designed intelligent module for detecting signs of a threat to information security and the emergence of unreliable and/or anomalous data works in real time with a high accuracy of 97.53 %. It meets the requirements of modern production

Author Biographies

Irina Cherepanska, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Doctor of Technical Sciences, Professor

Department of Automation and Non-Destructive Testing Systems

Artem Sazonov, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

PhD, Associate Professor

Department of Automation Hardware and Software

Yuriy Kyrychuk, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute

Doctor of Technical Sciences, Associate Professor

Department of Automation and Non-Destructive Testing Systems

Petro Melnychuk, Zhytomyr Polytechnic State University

Doctor of Technical Sciences, Professor

Department of Manufacturing Engineering

Dmytro Melnychuk, Zhytomyr Polytechnic State University

Doctor of Economic Sciences, Professor

Department of Psychology and Social Welfare

Nataliia Nazarenko, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

PhD, Senior Lecturer

Department of Automation and Non-Destructive Testing Systems

Volodymyr Pryadko, Polissia National University

Department of Electrification, Production Automation and Engineering Ecology

Serhii Bakhman, Zhytomyr Polytechnic State University

PhD Student

Department of Manufacturing Engineering

Davyd Khraban, Zhytomyr Polytechnic State University

PhD Student

Department of Manufacturing Engineering

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Design of an intelligent module for detecting signs of information security threats and the emergence of unreliable data

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Published

2024-12-25

How to Cite

Cherepanska, I., Sazonov, A., Kyrychuk, Y., Melnychuk, P., Melnychuk, D., Nazarenko, N., Pryadko, V., Bakhman, S., & Khraban, D. (2024). Design of an intelligent module for detecting signs of information security threats and the emergence of unreliable data. Eastern-European Journal of Enterprise Technologies, 6(2 (132), 49–63. https://doi.org/10.15587/1729-4061.2024.317000

Issue

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

Section

Information technology

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Copyright (c) 2024 Irina Cherepanska, Artem Sazonov, Yuriy Kyrychuk, Petro Melnychuk, Dmytro Melnychuk, Nataliia Nazarenko, Volodymyr Pryadko, Serhii Bakhman, Davyd Khraban

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