Cybersecurity Resilience in IoT-Enabled Critical Infrastructures

A PRISMA Systematic Review and Bibliometric Analysis

Authors

DOI:

https://doi.org/10.56394/aris2.v6i2.68

Keywords:

cybersecurity resilience, Internet of Things (IoT), critical infrastructures; anomaly detection, machine learning, federated learning, cloud–edge security, PRISMA systematic review

Abstract

The increasing integration of IoT technologies into critical infrastructures has brought significant benefits in terms of automation, monitoring, and operational efficiency across sectors such as energy, healthcare, transportation, and industrial systems. At the same time, this transformation has substantially increased exposure to cyber threats, particularly in environments where cyber and physical processes are tightly coupled and service availability is critical. Conventional cybersecurity approaches, largely focused on prevention and perimeter defense, have shown limited effectiveness in highly distributed, heterogeneous, and dynamic IoT-based infrastructures. In this context, the notion of cybersecurity resilience has emerged as a key paradigm, emphasizing the ability of systems to withstand attacks, adapt to adverse conditions, and recover essential functions rather than relying solely on intrusion prevention. This paper presents a systematic literature review conducted in accordance with the PRISMA 2020 guidelines, focusing on cybersecurity resilience in IoT-enabled critical infrastructures. An initial set of 244 publications was identified through major scientific databases, from which nine primary studies were selected following a rigorous screening and eligibility process. The review is complemented by a bibliometric analysis that examines publication trends, research focus, and the evolution of resilience-oriented security approaches over time. The findings indicate a distinct transformation in the direction of unified security frameworks, from having separate intrusion detection mechanisms. Nevertheless, current integration efforts still reveal substantial differences in maturity and validation, particularly in operational environments.

References

[1] Ahmed, A.A.; Farhan, K.; Jabbar, W.A.; Al-Othmani, A.; Abdulrahman, A.G. IoT Forensics: Current Perspectives and Future Directions. Sensors 2024, 24, 5210. https://doi.org/10.3390/s24165210 DOI: https://doi.org/10.3390/s24165210

[2] A. Humayed, J. Lin, F. Li, and B. Luo, “Cyber-Physical Systems Security - A Survey,” IEEE Internet of Things Journal, vol. 4, no. 6, pp. 1802–1831, Dec. 2017. DOI: https://doi.org/10.1109/JIOT.2017.2703172

[3] European Union Agency for Cybersecurity (ENISA), Threat Landscape for IoT, ENISA, Athens, Greece, 2022.

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Published

2026-11-02

How to Cite

[1]
L. M. Pires, “Cybersecurity Resilience in IoT-Enabled Critical Infrastructures: A PRISMA Systematic Review and Bibliometric Analysis”, ARIS2-Journal, vol. 6, no. 2, pp. 3–15, Nov. 2026.

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