МЕТОДИ ЗАБЕЗПЕЧЕННЯ ЦІЛІСНОСТІ ОБРОБКИ ТА ПЕРЕДАЧІ ДАНИХ У ПРОМИСЛОВИХ СИСТЕМАХ АВТОМАТИЗАЦІЇ

Ярослав Корпань; Євген Федоров; Ольга Нечипоренко

doi:10.20535/kpisn.2026.3.361520

Vol. 144 · Issue 3 · 2026 Sep 29, 2026 article

METHODS FOR ENSURING THE INTEGRITY OF DATA PROCESSING AND TRANSMISSION IN INDUSTRIAL AUTOMATION SYSTEMS

Yaroslav Korpan Corresponding Department of Robotics and Specialized Computer Systems, Faculty of information technologies and systems, Cherkassy State Technological University, Cherkasy, Ukraine Ukraine

Eugene Fedorov Department of Statistics and Applied Mathematics, Faculty of information technologies and systems, Cherkassy State Technological University, Cherkasy, Ukraine Ukraine

Olga Nechyporenko Department Informational Security and Computer Engineering, Faculty of information technologies and systems, Cherkassy State Technological University, Cherkasy, Ukraine Ukraine

PublishedSep 29, 2026

PDF (Ukrainian)

KPISN 3 VOL 144 · 3

VOL 144 · ISS 3 · 2026 View issue

Abstract

Background . Modern industrial control systems are characterized by a high level of integration between information and physical processes and the use of distributed computing environments, which complicates the task of ensuring data integrity. Existing approaches are primarily focused on network security and access control and do not sufficiently account for the cyber-physical nature of these systems. Therefore, the problem of ensuring comprehensive data integrity at all stages (transmission, processing, storage) remains unresolved, especially in the face of modern cyber threats and real-time requirements, which can lead not only to informational but also to physical disruptions of technological processes. Objective - formulate a generalized approach to ensuring data integrity in industrial control systems that enables the effective detection and prevention of integrity violations during the transmission and processing of information, taking into account the cyber-physical nature of real-time systems. Methods involves analyzing threats, formalizing a model, and systematizing methods for ensuring data integrity in industrial control systems, taking into account their application at various levels of the system Results . A generalized approach to ensuring data integrity in industrial control systems has been formulated, taking into account their cyber-physical nature. A classification of integrity assurance methods is proposed based on system functional levels and operating principles. The limitations of existing approaches are identified, and the necessity of their comprehensive application is justified. The results obtained can be used to improve the effectiveness of detecting and preventing integrity violations in modern industrial automation systems. Conclusions . This paper analyzes modern approaches to ensuring data integrity in industrial control systems and identifies their main limitations, which stem from insufficient consideration of the cyber-physical nature of these systems. A generalized approach is formulated and a classification of methods is proposed, allowing existing solutions to be systematized by levels of operation. The feasibility of the comprehensive application of multi-level methods to enhance system resilience against integrity breaches is demonstrated. The results obtained can be used to improve approaches to the protection of industrial automation systems.

Keywords

#industrial automation systems #SCADA systems #data integrity #ICS cybersecurity #machine learning #cyber-physical systems

References

Ya. V. Korpan, “Klasyfikatsiia zahroz informatsiinii bezpetsi v kompiuternykh systemakh pry viddalenii obrobtsi danykh”, Reiestratsiia, zberihannia i obrobka danykh, tom. 17, № 2, stor. 39–46, 2015.
DOI: https://doi.org/10.35681/1560-9189.2015.17.2.100318
D. Bhamare, M. Zolanvari, A. Erbad, R. Jain, K. Khan, N. Meskin, Cybersecurity for industrial control systems: A survey, 2019, Computers and Security, 89, Article 101677. DOI: https://doi.org/10.1016/j.cose.2019.101677
H. Srinivasan, M. Karimi, Threat based Security Controls to Protect Industrial Control Systems. arXiv:2501.13268 [cs.CR], 2025.
DOI: https://doi.org/10.48550/arXiv.2501.13268 .
K. Szymkowiak, Industrial Control Systems Security – Best Practices: Investigating best practices for securing ICS and SCADA systems from cyber threats. Distributed Learning and Broad Applications in Scientific Research, vol. 8, 2022.
URL: https://dlabi.org/index.php/journal/article/view/60
Bajwa, Ammar & Tonoy, Aleem Al Razee & Rana, Sohel & Ahmed, Ishtiaque, Cybersecurity In Industrial Control Systems: A Systematic Literature Review On AI-Based Threat Detection For SCADA And IOT Networks, 2025, 01(01):01-15.
DOI: https://doi.org/10.63125/1cr1kj17 .
Li, Y., Wu, S., & Pan, Q. Network Security in the Industrial Control System: A Survey. arXiv:2308.03478 [cs.CR], 2023. URL: https://arxiv.org/pdf/2308.03478
Muhammad Rizwan Asghar, Qinwen Hu, Sherali Zeadally, Cybersecurity in industrial control systems: Issues, technologies, and challenges, Computer Networks, Volume 165:106946, 2019. DOI: https://doi.org/10.1016/j.comnet.2019.106946 .
E. D. Knapp, & J.T. Langill Industrial Network Security: Securing Critical Infrastructure Networks for Smart Grid, SCADA, and Other Industrial Control Systems, 2014. DOI: https://doi.org/10.1016/B978-0-12-420114-9.00018-6 .
F.-K. Schachinger, T. Rosenstatter, and U. Pache, “PURITY: An Industry-Standard-Based Security Framework for IT-OT Convergence,” IEEE Access, 2026.
DOI: https://doi.org/10.1109/ACCESS.2026.3682366 .
R. K. S. Pillai, E. O’Connell, and P. Denny, “Role of Unified Namespace (UNS) and Digital Twins in Predictive and Adaptive Industrial Systems,” Machines, vol. 14, no. 2, Art. no. 252, 2026. DOI: https://doi.org/10.3390/machines14020252 .
M. G. Jaatun, M. A. Lundteigen, C. Thieme et al., “Security Aspects of Zones and Conduits in IEC 62443,” Journal of Cybersecurity and Privacy, vol. 6, no. 2, Art. no. 52, 2026. DOI: https://doi.org/10.3390/jcp6020052 .

Previous in issue AN APPROACH TO CONSTRUCTING AN INFORMATIVE FEATURE SPACE OF TECHNICAL INDICATORS FOR FINANCIAL PROCESSES BASED ON NEURAL NETWORK MODELS Next in issue METHODOLOGY FOR THE PARAMETRIC SYNTHESIS OF ZOOM-AFOCAL SYSTEMS BASED ON FIXED VARIOFOCAL LENSES

§ 06 — Related

[1] Ya. V. Korpan, “Klasyfikatsiia zahroz informatsiinii bezpetsi v kompiuternykh systemakh pry viddalenii obrobtsi danykh”, Reiestratsiia, zberihannia i obrobka danykh, tom. 17, № 2, stor. 39–46, 2015.

[2] DOI: https://doi.org/10.35681/1560-9189.2015.17.2.100318

[3] D. Bhamare, M. Zolanvari, A. Erbad, R. Jain, K. Khan, N. Meskin, Cybersecurity for industrial control systems: A survey, 2019, Computers and Security, 89, Article 101677. DOI: https://doi.org/10.1016/j.cose.2019.101677

[4] H. Srinivasan, M. Karimi, Threat based Security Controls to Protect Industrial Control Systems. arXiv:2501.13268 [cs.CR], 2025.

[5] DOI: https://doi.org/10.48550/arXiv.2501.13268 .

[6] K. Szymkowiak, Industrial Control Systems Security – Best Practices: Investigating best practices for securing ICS and SCADA systems from cyber threats. Distributed Learning and Broad Applications in Scientific Research, vol. 8, 2022.

[7] URL: https://dlabi.org/index.php/journal/article/view/60

[8] Bajwa, Ammar & Tonoy, Aleem Al Razee & Rana, Sohel & Ahmed, Ishtiaque, Cybersecurity In Industrial Control Systems: A Systematic Literature Review On AI-Based Threat Detection For SCADA And IOT Networks, 2025, 01(01):01-15.

[9] DOI: https://doi.org/10.63125/1cr1kj17 .

[10] Li, Y., Wu, S., & Pan, Q. Network Security in the Industrial Control System: A Survey. arXiv:2308.03478 [cs.CR], 2023. URL: https://arxiv.org/pdf/2308.03478

[11] Muhammad Rizwan Asghar, Qinwen Hu, Sherali Zeadally, Cybersecurity in industrial control systems: Issues, technologies, and challenges, Computer Networks, Volume 165:106946, 2019. DOI: https://doi.org/10.1016/j.comnet.2019.106946 .

[12] E. D. Knapp, & J.T. Langill Industrial Network Security: Securing Critical Infrastructure Networks for Smart Grid, SCADA, and Other Industrial Control Systems, 2014. DOI: https://doi.org/10.1016/B978-0-12-420114-9.00018-6 .

[13] F.-K. Schachinger, T. Rosenstatter, and U. Pache, “PURITY: An Industry-Standard-Based Security Framework for IT-OT Convergence,” IEEE Access, 2026.

[14] DOI: https://doi.org/10.1109/ACCESS.2026.3682366 .

[15] R. K. S. Pillai, E. O’Connell, and P. Denny, “Role of Unified Namespace (UNS) and Digital Twins in Predictive and Adaptive Industrial Systems,” Machines, vol. 14, no. 2, Art. no. 252, 2026. DOI: https://doi.org/10.3390/machines14020252 .

[16] M. G. Jaatun, M. A. Lundteigen, C. Thieme et al., “Security Aspects of Zones and Conduits in IEC 62443,” Journal of Cybersecurity and Privacy, vol. 6, no. 2, Art. no. 52, 2026. DOI: https://doi.org/10.3390/jcp6020052 .

METHODS FOR ENSURING THE INTEGRITY OF DATA PROCESSING AND TRANSMISSION IN INDUSTRIAL AUTOMATION SYSTEMS

Abstract

Keywords

References

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