Fuzzy logic-based security risk assessment in wireless sensor networks of Industrial IoT

Olena Semenova; Natalia Kryvinska; Olha Voitsekhovska; Andrii Dzhus; Volodymyr Martyniuk

doi:10.35784/iapgos.8133

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Published: Jun 30, 2026

DOI: https://doi.org/10.35784/iapgos.8133

Issue Vol. 16 No. 2 (2026)

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Fuzzy logic-based security risk assessment in wireless sensor networks of Industrial IoT
Olena Semenova, Natalia Kryvinska, Olha Voitsekhovska, Andrii Dzhus, Volodymyr Martyniuk

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Authors

Olena Semenova

semenova.o.o@vntu.edu.ua

Vinnytsia National Technical University, Ukraine

https://orcid.org/0000-0001-5312-9148

Natalia Kryvinska

natalia.kryvinska@fm.uniba.sk

Comenius University in Bratislava, Slovakia

https://orcid.org/0000-0003-3678-9229

Olha Voitsekhovska

o_voytsekhovska@vntu.edu.ua

Vinnytsia National Technical University, Ukraine

https://orcid.org/0000-0001-8504-1204

Andrii Dzhus

dzhuz1988@gmail.com

Vinnytsia National Technical University, Ukraine

https://orcid.org/0009-0005-3583-5766

Volodymyr Martyniuk

vm4ukr@gmail.com

Vinnytsia National Technical University, Ukraine

https://orcid.org/0009-0006-8421-0348

Abstract

Recent years have seen the widespread deployment of wireless sensor networks (WSN), low-cost sensors, industrial clouds and industrial robots. These technological advancements have facilitated the development of Industrial Internet of Things (IIoT) technologies and fostered the emergence of novel digital applications. Thus, the IIoT is a technological concept involving the communication and interaction of mobile devices over wireless networks. Due to the numerous limitations of wireless sensor networks, security is one of the main issues. In the context of interconnected smart devices, the assumption of control over a single device has the potential to compromise the security of the entire network. The identification of these vulnerabilities can be enhanced by the implementation of remote diagnostics for IIoT devices. Whilst Artificial Intelligence (AI) finds extensive application in the solution of complex scientific, technical and practical issues, the present study investigates its use in wireless sensor networks of IIoT. Fuzzy systems, neural networks and genetic algorithms are three examples of AI techniques that are frequently used in wireless networks to improve their optimization and management. This paper proposes a fuzzy logic-based approach that allows intelligent assessment of the security risk levels of IIoT devices. Thus, a fuzzy inference system (FIS) that evaluates the security risk level of an IIoT device was developed. Its parameters were established, including the input and output variables and their membership functions. The developed FIS was optimized thorough other AI techniques. The efficacy of the FIS was evaluated through the use of a computer simulation in the MATLAB.

Keywords:

security, WSN, IoT, fuzzy logic

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Semenova, O., Kryvinska, N., Voitsekhovska, O., Dzhus, A., & Martyniuk, V. (2026). Fuzzy logic-based security risk assessment in wireless sensor networks of Industrial IoT. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 16(2), 76–83. https://doi.org/10.35784/iapgos.8133

Fuzzy logic-based security risk assessment in wireless sensor networks of Industrial IoT

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