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Intrusion Detection Systems from IT to IIoT: Survey and Taxonomy

Ali Lamjid1,*, Khairul Akram Zainol Ariffin1,*, Mohd Juzaiddin Ab Aziz2, Nor Samsiah Sani3

1 Center for Cybersecurity, FTSM, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
2 Center for Software Technology and Management, FTSM, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
3 Center for Artificial Intelligence and Technology, FTSM, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

* Corresponding Authors: Ali Lamjid. Email: email; Khairul Akram Zainol Ariffin. Email: email

Journal of Cyber Security 2026, 8, 211-240. https://doi.org/10.32604/jcs.2026.077850

Abstract

The convergence of Operational Technology (OT) and Information Technology (IT) within Critical Infrastructures gives rise to complex and heterogeneous network architectures in the Industrial Internet of Things (IIoT). Traditional Intrusion Detection Systems (IDS), designed for conventional IT environments, are suited for mitigating vulnerabilities inherent in these systems; however, they often fail to address vulnerabilities intrinsic to heterogeneous IIoT architectures, most notably adversarial threats. To address this challenge, this study undertakes a systematic review of 23 representative papers published between 2016 and 2025, analyzing the IIoT-based IDS approaches. Distinguishing itself from existing reviews, this work classifies IDS approaches based on deployment architecture, detection methodology, and security threat types, thereby identifying a critical gap in current defensive capabilities. This analytical framework reveals a critical deficiency in current defense mechanisms against sophisticated threats such as adversarial attacks. The proposed taxonomy provides a foundational framework for the rational design of robust hybrid IDS solutions that can secure both legacy supervisory control and data acquisition (SCADA) systems and modern smart devices. Ultimately, these findings provide a strategic road-map for researchers and practitioners to advance Cybersecurity resilience in the rapidly maturing IIoT platforms.

Keywords

Cybersecurity; intrusion detection system; IT; OT; industrial IoT; taxonomy

Cite This Article

APA Style
Lamjid, A., Ariffin, K.A.Z., Aziz, M.J.A., Sani, N.S. (2026). Intrusion Detection Systems from IT to IIoT: Survey and Taxonomy. Journal of Cyber Security, 8(1), 211–240. https://doi.org/10.32604/jcs.2026.077850
Vancouver Style
Lamjid A, Ariffin KAZ, Aziz MJA, Sani NS. Intrusion Detection Systems from IT to IIoT: Survey and Taxonomy. J Cyber Secur. 2026;8(1):211–240. https://doi.org/10.32604/jcs.2026.077850
IEEE Style
A. Lamjid, K. A. Z. Ariffin, M. J. A. Aziz, and N. S. Sani, “Intrusion Detection Systems from IT to IIoT: Survey and Taxonomy,” J. Cyber Secur., vol. 8, no. 1, pp. 211–240, 2026. https://doi.org/10.32604/jcs.2026.077850



cc Copyright © 2026 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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